This file contains the results of a bib search, hand-pruned to
eliminate false hits, leaving 287 legitimate hits. The database only
goes back to 1986, but my original scale space article appeared in
'83, so we're missing a few of years' worth. In any event, the
original citation is
Andrew Witkin. Scale space filtering. In Proc. International
Joint Conference on Artificial Intelligence, Karlsruhe, 1983.
------------------------------------------------------------
Author Fatemi-Ghomi, N.; Palmer, P.L.; Petrou, M.;
Dept. of Electron. & Electr. Eng., Surrey Univ., Guildford, UK
Title Multiresolution texture segmentation
Source IEE Colloquium on 'Texture Classification: Theory and
Applications (Digest No.1994/178); Part: London, UK; Part: 7
Oct. 1994;
Sponsored by: IEE;
IEE Colloquium on 'Texture Classification: Theory and
Applications (Digest No.1994/178);
London, UK;
IEE;
38;
1994; pp. 2/1-3
Abstract One of the major developments in texture segmentation in recent
years has been the use of multiresolution descriptions of these
images. One may consider this multiresolution description to
provide information about the image contained in ever smaller
regions of the frequency domain, and thus provides a powerful
tool for the discrimination of similar textures. It has recently
been established that use of scale-space-filtering by ever wider
filters, is equivalent to a decomposition of the image in terms
of wavelets. The big advantage of the wavelet description of an
image is that it is invertible. In this paper we use successive
transformations of textured images in terms of wavelets to
produce lower resolution descriptions of the image. This
procedure can be thought of as dynamically focussing on the
important region of the frequency domain for the particular
texture in the image
Thesaurus image segmentation; image texture
Other Terms texture segmentation; multiresolution descriptions; frequency
domain; scale-space-filtering; successive transformations;
textured images
ClassCodes C1250; C5260B
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4824740
AbstractNos. C9412-1250-334
References 3
Country Pub. UK
date 1232
------------------------------------------------------------
Author Ji Yu Shi; Hung Tat Tsui;
Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Shatin, Hong
Kong
Title Scale space filtering by Fejer kernel
Source Proceedings of ICSIPNN '94. International Conference on Speech,
Image Processing and Neural Networks; Part: vol.2; Part: Hong
Kong; Part: 13-16 April 1994;
Sponsored by: IEEE Signal Process. Soc.; HKIE Electron. Div.;
IEE Hong Kong Centre;
ISSIPNN '94. 1994 International Symposium on Speech, Image
Processing and Neural Networks Proceedings (Cat. No.94TH0638-7);
New York, NY, USA;
IEEE;
2 vol. (xxxvii+xi+797);
1994; pp. 638-41 vol.2
Abstract A multiscale description of the raw signal data must be first
obtained before more abstract representations and descriptions
are generated. Many unsuccessful attempts have been made to let
this initial description be as compact and complete as possible.
We propose a new filtering kernel called Fejer kernel to try to
tackle this problem. The behaviors of signals' features in
different scales are investigated in Fejer scale space-(x, Delta
) plane. Simulation results are shown to demonstrate this new
multiscale description for a signal. It compares favorably with
Gaussian scale space filtering in that it brings out the main
features of the signal under large scales. Gaussian filtering
just makes every feature smoother. Further investigation to
refine this new multiscale signal description is under development
Thesaurus filtering and prediction theory; signal processing
Other Terms Fejer kernel; scale space filtering; signal data; multiscale
description; abstract representations; filtering kernel; Fejer
scale space; simulation results; Gaussian scale space filtering;
multiscale signal description; signal representation
ClassCodes B6140; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4824557
AbstractNos. B9412-6140-269; C9412-1260-245
ISBN or SBN 0 7803 1865 X
References 12
U.S. Copyright Clearance Center Code
0 7803 1865 X/94/$3.00
Country Pub. USA
date 1226
------------------------------------------------------------
Author Wong, Y.-f.;
Lawrence Livermore Nat. Lab., Livermore, CA, USA
Title A clustering filter for scale-space filtering and image
restoration
Source Proceedings of IEEE Conference on Computer Vision and Pattern
Recognition; Part: New York, NY, USA; Part: 15-17 June 1993;
Sponsored by: IEEE Comput. Soc. Tech. Committee on Pattern Anal.
& Mach. Intelligence;
Proceedings. 1993 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.93CH3309-2);
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xviii+804;
1993; pp. 668-9
Abstract A nonlinear clustering filter is derived using the maximum
entropy principle. This filter is governed by a single-scale
parameter and uses local characteristics in the data to determine
the scale parameter in the output space. It provides a mechanism
for removing impulsive noise, preserving edges, and improving
smoothing of nonimpulsive noise. It also presents a scheme for
nonlinear scale-space filtering. Comparisons with Gaussian scale-
space filtering are made using real images. It is demonstrated
that the clustering filter gives much better results
Thesaurus entropy; filtering and prediction theory; image recognition;
image reconstruction; parameter estimation
Other Terms impulsive noise removal; edge preservation; nonimpulsive noise
smoothing; image restoration; nonlinear clustering filter;
maximum entropy principle; single-scale parameter; scale
parameter; output space; nonlinear scale-space filtering
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4823739
AbstractNos. B9412-6140C-424; C9412-1250-282
ISBN or SBN 0 8186 3880 X
References 5
U.S. Copyright Clearance Center Code
1063-6919/93/$03.00
Country Pub. USA
date 1215
------------------------------------------------------------
Author Mokhtarian, F.;
NTT Basic Res. Lab., Tokyo, Japan
Title Multi-scale, torsion-based shape representations for space curves
Source Proceedings of IEEE Conference on Computer Vision and Pattern
Recognition; Part: New York, NY, USA; Part: 15-17 June 1993;
Sponsored by: IEEE Comput. Soc. Tech. Committee on Pattern Anal.
& Mach. Intelligence;
Proceedings. 1993 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.93CH3309-2);
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xviii+804;
1993; pp. 660-1
Abstract Space curves are efficient, highly descriptive features of 3-D
objects. A new multiscale shape representation (the resampled
torsion scale space or TSS image) for space curves suitable for
recognition of a noisy curve at any scale or orientation is
introduced. A two-phase matching algorithm consisting of TSS
matching (using extrema of TSS zero-crossing contours) followed
by transformation parameter optimization demonstrates the
usefulness of the representation in recognition tasks
Thesaurus image recognition; image sequences
Other Terms noisy curve recognition; zero-crossing contour extrema; torsion-
based shape representations; space curves; 3-D objects;
multiscale shape representation; resampled torsion scale space;
TSS image; two-phase matching algorithm; transformation
parameter optimization
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4823735
AbstractNos. B9412-6140C-421; C9412-1250-278
ISBN or SBN 0 8186 3880 X
References 2
U.S. Copyright Clearance Center Code
1063-6919/93/$03.00
Country Pub. USA
date 1215
------------------------------------------------------------
Author Lions, P.-L.;
CEREMADE, Paris IX Univ., France
Title Axiomatic derivation of image processing models
Source Mathematical Models & Methods in Applied Sciences;
Math. Models Methods Appl. Sci. (Singapore);
vol.4, no.4;
Aug. 1994; pp. 467-75
Abstract We briefly review the derivation due to Alvarez, Guichard, Morel
(1993) and the author of mathematical models in image processing.
We deduce from classical axioms in computer vision some nonlinear
partial differential equations of evolution type that correspond
to general multi-scale analysis (scale-space). We also obtain
specific nonlinear models that satisfy additional invariances
which are relevant for the analysis of images
Thesaurus computer vision; nonlinear differential equations; partial
differential equations
Other Terms image processing models; computer vision; nonlinear partial
differential equations; multi-scale analysis; scale-space
ClassCodes C1250; C5260B; C4170
Article Type Theoretical / Mathematical
Coden MMMSEU
Language English
RecordType Journal
ControlNo. 4822130
AbstractNos. C9412-1250-230
ISSN 02182025
References 24
Country Pub. Singapore
date 1230
------------------------------------------------------------
Author Theimer, W.M.; Mallot, H.A.;
Inst. fur Neuroinf., Ruhr-Univ., Bochum, Germany
Title Phase-based binocular vergence control and depth reconstruction
using active vision
Source CVGIP: Image Understanding;
CVGIP, Image Underst. (USA);
vol.60, no.3;
Nov. 1994; pp. 343-58
Abstract We present a technique for guiding vergence movements for an
active stereo camera system and for calculating dense disparity
maps. Both processes are described in the same theoretical
framework based on phase differences in complex Gabor filter
responses, modeling receptive field properties in the visual
cortex. While the camera movements are computed with input images
of coarse spatial resolution, the disparity map calculation uses
a finer resolution in the scale space. The correspondence problem
is solved implicitly by restricting the disparity range around
zero disparity (Panum's area in the human visual system). The
vergence process is interpreted as a mechanism to minimize global
disparity, thereby setting a 3D region of interest for subsequent
disparity detection. The disparity map represents smaller local
disparities as an important cue for depth perception.
Experimental data for the integrated performance of vergence in
natural scenes followed by disparity map calculations are
presented
Thesaurus computer vision; stereo image processing; visual perception
Other Terms phase-based binocular vergence control; depth reconstruction;
active vision; guiding vergence movements; active stereo camera
system; dense disparity maps; phase differences; complex Gabor
filter responses; receptive field properties; visual cortex;
camera movements; input images; spatial resolution;
correspondence problem; human visual system; Panum's area;
zero disparity; 3D region; depth perception; integrated
performance; natural scenes
ClassCodes B6140C; C5260B
Article Type Theoretical / Mathematical
Coden CIUNEJ
Language English
RecordType Journal
ControlNo. 4822092
AbstractNos. B9412-6140C-361; C9412-5260B-232
ISSN 10499660
References 26
U.S. Copyright Clearance Center Code
1049-9660/94/$6.00
Country Pub. USA
date 1233
------------------------------------------------------------
Author Hwang, W.-L.; Mallat, S.;
Dept. of Comput. Sci., New York Univ., NY, USA
Title Characterization of self-similar multifractals with wavelet maxima
Source Applied and Computational Harmonic Analysis;
Appl. Comput. Harmon. Anal. (USA);
vol.1, no.4;
Sept. 1994; pp. 316-28
Abstract Self-similar multifractals have a wavelet transform whose maxima
define self-similar curves in the scale-space plane. We introduce
an algorithm that recovers the affine self-similarity parameters
through a voting procedure in the corresponding parameter space.
The voting approach is robust with respect to renormalization
noise and can recover the value of parameters having random
fluctuations. We describe numerical applications to Cantor
measures, dyadic multifractals, and the study of diffusion
limited aggregates
Thesaurus fractals; wavelet transforms
Other Terms self-similar multifractals; wavelet maxima; wavelet transform;
self-similar curves; scale-space plane; affine self-similarity
parameters; voting procedure; parameter space; renormalization
noise; random fluctuations; Cantor measures; dyadic
multifractals; diffusion limited aggregates
ClassCodes B0230; B0290Z; C1130; C4190
Article Type Theoretical / Mathematical
Coden ACOHE9
Language English
RecordType Journal
ControlNo. 4812736
AbstractNos. B9412-0230-002; C9412-1130-001
ISSN 10635203
References 13
U.S. Copyright Clearance Center Code
1063-5203/94/$6.00
Country Pub. USA
date 1231
------------------------------------------------------------
Author Jang, B.K.;
Health Sci. Res. Lab., Eastman Kodak Co., Rochester, NY, USA
Title Gaussian and morphological scale space for shape analysis of
medical images
Source 1993 IEEE Conference Record Nuclear Science Symposium and Medical
Imaging Conference; Part: vol.2; Part: San Francisco, CA, USA; P
art: 31 Oct.-6 Nov. 1993;
1993 IEEE Conference Record. Nuclear Science Symposium and
Medical Imaging Conference (Cat. No.93CH3374-6);
New York, NY, USA;
IEEE;
3 vol. 1930;
1993; pp. 1327-31 vol.2
Editor Klaisner, L.
Abstract The construction of scale space requires the smoothing of the
given image to generate a set of corresponding images at other
coarser scales, and the extraction of features at these scales.
Various methods of smoothing, combined with various feature
extractors, will result in drastically different scale space
representations. The particular application and desired criteria
determine the choice of smoothing and feature extractor. Here the
author first puts forward a framework for the scale space
representation. Then he focuses on the Gaussian and morphological
scale space for planar shape analysis of medical images. The
discussion of the various scale space methods is organized into
three categories - boundary approach, region approach, and hybrid
approach. Properties, limitations, performance, and applications
of these scale space methods are discussed
Thesaurus feature extraction; image segmentation; medical image processing
Other Terms morphological scale space; medical images shape analysis;
Gaussian space; planar shape analysis; boundary approach;
region approach; hybrid approach; feature extractor; smoothing
ClassCodes A8710; A8760; A8770E
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4811940
AbstractNos. A9424-8710-004
ISBN or SBN 0 7803 1487 5
References 13
U.S. Copyright Clearance Center Code
0 7803 1487 5/94/$04.00
Country Pub. USA
date 1219
------------------------------------------------------------
Author Topkar, V.; Sood, A.K.; Kjell, B.;
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Title Performance analysis of 1-D scale-space algorithms for pulse
detection in noisy image scans
Source CVGIP: Image Understanding;
CVGIP, Image Underst. (USA);
vol.60, no.2;
Sept. 1994; pp. 191-209
Abstract Scale-space representation is a topic of active research in
computer vision. The focus of the research so far has been on
coarse-to-line focusing methods, image reconstruction, and
computational aspects. However, not much work has been done on
the signal detection problem, i.e., detecting the presence or
absence of signal models from noisy image scans using the scale-
space. In this paper we propose four 1-D signal detection
algorithms for separating pulse signals in an image scan from the
background in the scale-space domain. These algorithms do not
need any thresholding to detect the zero-crossings (zc's) at any
of the scales
Thesaurus computer vision; image reconstruction; noise; signal detection
Other Terms 1-D scale-space algorithms; pulse detection; noisy image scans;
computer vision; image reconstruction; signal detection; zero-
crossings; image scan
ClassCodes B6140C; C5260B; C1250
Article Type Practical
Coden CIUNEJ
Language English
RecordType Journal
ControlNo. 4803851
AbstractNos. B9412-6140C-107; C9412-5260B-064
ISSN 10499660
References 17
U.S. Copyright Clearance Center Code
1049-9660/94/$6.00
Country Pub. USA
date 1231
------------------------------------------------------------
Author Kelch, J.; Wein, B.;
Rogowski-Inst. for Electr. Eng., Tech. Hochschule Aachen, Germany
Title Segmentation of the tongue surface in ultrasonic images using
modified scale space filtering
Source Proceedings of IEEE Ultrasonics Symposium; Part: vol.2; Part:
Baltimore, MD, USA; Part: 31 Oct.-3 Nov. 1993;
Sponsored by: Ultrasonics Ferroelectric & Frequency Control Soc;
IEEE 1993 Ultrasonics Symposium Proceedings (Cat. No.93CH3301-9);
New York, NY, USA;
IEEE;
2 vol. 1270;
1993; pp. 947-50 vol.2
Editor Levy, M.; McAvoy, B.R.
Abstract For the detection of motility disturbances during swallowing and
articulation B-mode sonography is used. In general these images
of a median sagittal plane through the tongue and the floor of
the mouth are manually contoured by the physician, because it is
quite difficult to get subtle information concerning tongue
movement and motility from the real-time video images. The
digitised images built a spatiotemporal space with a depth of
about 70 frames. The authors' application demonstrates a way to
extract the tongue contour automatically. They use a modified
scale space filter for edge detection. In this way contour
segments of the tongue dorsum and other object parts are
extracted. A model of the tongue supports identification of the
tongue segments and interpolation of the plane in the
spatiotemporal space. A virtual three-dimensional view of these
contours of the spatiotemporal space assists the physician to a
diagnosis of the movement disturbance
Thesaurus acoustic signal processing; biomedical ultrasonics; edge
detection; filtering and prediction theory; image segmentation;
medical image processing; patient diagnosis
Other Terms tongue surface; ultrasonic images; modified scale space
filtering; motility disturbances; swallowing; articulation; B-
mode sonography; median sagittal plane; mouth; tongue movement;
spatiotemporal space; digitised images; tongue contour; edge
detection; virtual three-dimensional view; diagnosis
ClassCodes A8760B; A8770E; A4360; B7510B; B7820; B6140C; C7330; C1250;
C1260; C5260B
Article Type Practical
Language English
RecordType Conference
ControlNo. 4800558
AbstractNos. A9423-8760B-012; B9412-7510B-011; C9412-7330-020
ISBN or SBN 0 7803 1278 3
References 7
U.S. Copyright Clearance Center Code
1051-0117/93/$4.00
Country Pub. USA
date 1219
------------------------------------------------------------
------------------------------------------------------------
Author Lefevre, M.; Preteux, F.; Lavayssiere, B.;
Dpt. Image, ENST, Paris, France
Title Radiographic inspection, defects segmentation and multiscale
analysis
Source Image Algebra and Morphological Image Processing V; Part: San
Diego, CA, USA; Part: 25-26 July 1994;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2300;
1994; pp. 122-32
Abstract In radiographic inspection used by Electricite De France (EDF)
for pipe control in nuclear power plants, pipe radiographs are
digitized according to a well-defined protocol. The aim of EDF
consists of developing a non-destructive testing system for
identifying defects. Because of the poor quality of the digitized
images, the segmentation problem is very difficult to solve. In
this paper, we propose an approach based on a multiscale analysis
to simultaneously achieve defect-enhancement and noise-filtering
and perform accurate defect segmentation using mathematical
morphology. The principle consists of defining a one-parameter
family of operators which are successively applied to the
digitized images after drift-removal. Equivalently, the
multiscale analysis can be expressed as the solution of an
evolution equation, whose analytical form is conditioned by the
specific properties of the operators (e.g. mean curvature motion,
affine scale-space). This results in a family of images with
increasing smoothness and consistent edge preservation. Within
this framework, we propose a global critical scale estimation via
a multiscale analysis of second order local moments of the image.
This value minimizes noise ratio without altering edges.
Following the filtering step, the final segmentation is easily
performed via a morphological approach based on the connection
cost concept. The developed method has been tested on a set of
radiographs including various defect patterns, leading to
impressive segmentation results. Robustness with respect to noise
ratio and optimal scale are discussed
Thesaurus edge detection; flaw detection; image segmentation;
mathematical morphology; noise; parameter estimation;
radiography
Other Terms radiographic inspection; defects segmentation; multiscale
analysis; Electricite De France; pipe control; nuclear power
plants; EDF; non-destructive testing system; digitized images;
edge fuzziness; defect-enhancement; noise-filtering;
mathematical morphology; drift-removal; evolution equation;
analytical form; mean curvature motion; affine scale-space;
consistent edge preservation; global critical scale estimation;
second order local moments; final segmentation
ClassCodes B6140C; B0590; C1250; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4791799
AbstractNos. B9411-6140C-528; C9411-1250-357
ISSN 0277786X
References 25
U.S. Copyright Clearance Center Code
0 8194 1624 X/94/$6.00
Country Pub. USA
date 1229
------------------------------------------------------------
Author Peters, R.A., II; Nichols, J.A.;
Dept. of Electr. Eng., Vanderbilt Univ., Nashville, TN, USA
Title Properties of image sequences generated through opening residuals
Source Image Algebra and Morphological Image Processing V; Part: San
Diego, CA, USA; Part: 25-26 July 1994;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2300;
1994; pp. 57-68
Abstract A type of Euclidean granulometry is the sequence of images
created through the opening of a single image with a family of
mutually open structuring elements. The sequence is a
morphological analogue of linear scale space. In such a
granulometry, the minimum size of features increases in
successive images, whereas in scale space the maximum spatial
frequency decreases, and the images become increasingly lowpass.
The opening spectrum is the image sequence created by computing
the differences between successive images in a Euclidean
granulometry. Whereas the difference sequence from scale space
has a Laplacian bandpass characteristic, the opening spectrum
does not have analogous size band-limited properties. Moreover,
the images in an opening spectrum are usually not open. One can
create a size band-limited sequence analogous to a Laplacian
sequence through recursive opening of the tophat - the residual
difference between the image and its opening. The recursion is to
open the tophat with a smaller structuring element then to
subtract that opening from the tophat. We call the result the
tophat spectrum. This paper states and proves a number of
properties of the tophat and the tophat spectrum. These include:
the tophat is antiextensive and idempotent (but not increasing);
each image in the tophat spectrum is size-limited and open; the
structuring element family need not be mutually open to generate
a tophat spectrum; if the SE family is mutually open, and the
original image is binary, each image in the tophat spectrum
includes the open part of the corresponding image from the
opening spectrum; and, the tophat spectrum is identical to the
opening spectrum created with a family of flat, one-dimensional
structuring elements
Thesaurus image sequences; mathematical morphology; transforms
Other Terms image sequences; opening residuals; Euclidean granulometry;
single image; open structuring elements; morphological analogue;
linear scale space; feature size; scale space; maximum
spatial frequency; opening spectrum; successive images;
difference sequence; tophat; size band-limited sequence;
recursive opening; antiextensive; residual difference; tophat
spectrum; idempotent; size-limited image; flat one-dimensional
structuring elements
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4791793
AbstractNos. B9411-6140C-522; C9411-1250-352
ISSN 0277786X
References 17
U.S. Copyright Clearance Center Code
0 8194 1624 X/94/$6.00
Country Pub. USA
date 1229
------------------------------------------------------------
Author Bijaoui, A.;
Obs. de la Cote d'Azur, Nice, France
Title Partial reconstruction and astronomical image inventory by the
wavelet transform
Source Proceedings of 7th International Conference on Image Analysis and
Processing; Part: Monopoli, Italy; Part: 20-22 Sept. 1993;
Proceedings of the 7th International Conference on Image Analysis
and Processing. Progress in Image Analysis and Processing III;
Singapore;
World Scientific;
xxiv+733;
1994; pp. 411-16
Editor Impedovo, S.
Abstract We need a vision model in order to process large astronomical
images. Classical models, used on many sets of images, failed to
bring a complete analysis because they are based on a single
scale for the adapted smoothing and for the background mapping.
That lead us to introduce a new vision model based on the wavelet
transform, which splits the image in scale-space, allowing us to
detect objects of different sizes. The discrete wavelet transform
is obtained by the so-called "a trous" algorithm. We choose the
wavelet function resulting from the difference between two
successive B-spline approximations. We define an object as a
subtree resulting from the image segmentation in wavelet space.
The main steps of the vision procedure are: (i) the wavelet
transform of the image, (ii) scale/scale thresholding of the
wavelet images, (iii) field labelling of the wavelet images, and
(iv) object extraction. We have built a partial reconstruction
algorithm which provides an image for each object. It is easy to
compute any desired parameter from any object. Our experiments
showed that the detection quality is very good, and this method
showed low dispersion for photometric measurements
Thesaurus astronomical photometry; astronomy computing; computer vision;
image reconstruction; image segmentation; wavelet transforms
Other Terms partial image reconstruction; astronomical image inventory;
discrete wavelet transform; vision model; adapted smoothing;
background mapping; scale-space; astronomical object detection;
a trous algorithm; successive B-spline approximations; subtree;
image segmentation; scale/scale thresholding; field labelling;
object extraction; detection quality; dispersion;
photometric measurements
ClassCodes A9575M; A9575P; A9575D; A4230V; C7350; C5260B; C1130
Article Type Practical; Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4784587
AbstractNos. A9422-9575-006; C9411-7350-011
ISBN or SBN 981 02 1552 5
References 14
Country Pub. Singapore
date 1218
------------------------------------------------------------
Author Sapiro, G.; Bruckstein, A.M.;
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa,
Israel
Title A B-spline based affine invariant multiscale shape representation
Source Proceedings of 7th International Conference on Image Analysis and
Processing; Part: Monopoli, Italy; Part: 20-22 Sept. 1993;
Proceedings of the 7th International Conference on Image Analysis
and Processing. Progress in Image Analysis and Processing III;
Singapore;
World Scientific;
xxiv+733;
1994; pp. 137-44
Editor Impedovo, S.
Abstract Multiscale representations constitute an important topic in
different fields as computer vision, CAD, and image processing.
In this work, a multiscale representation of planar shapes is
described. The approach is based on computing B-splines of
increasing orders, and therefore is automatically affine
invariant. The resulting representation satisfies all the basic
scale-space properties at least in a qualitative form, and is
simple to implement
Thesaurus CAD; computer vision; splines (mathematics)
Other Terms B-spline based affine invariant multiscale shape representation;
computer vision; CAD; image processing; planar shapes; scale-
space properties
ClassCodes B6140C; B0290F; C5260B; C4130
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4784549
AbstractNos. B9411-6140C-290; C9411-5260B-232
ISBN or SBN 981 02 1552 5
References 23
Country Pub. Singapore
date 1218
------------------------------------------------------------
Author Theimer, W.M.; Mallot, H.A.;
Inst. fur Neuroinf., Ruhr-Univ., Bochum, Germany
Title Vergence guided depth reconstruction using a phase method
Source Proceedings of Sixth International Conference on Neural Networks
and their Industrial and Cognitive Applications; Part: Nimes,
France; Part: 25-29 Oct. 1993;
Sponsored by: AFIA; ARC; IFIP; JSAI & SEE; EERIE; et al;
Sixth International Conference. Neural Networks and their
Industrial and Cognitive Applications. NEURO-NIMES 93 Conference
Proceedings and Exhibition Catalog;
Nanterre, France;
EC2;
500;
1993; pp. 299-308
Abstract We present a technique to guide vergence movements for an active
stereo camera system and to calculate dense disparity maps. Both
processes are described in the same theoretical framework based
on phase differences in complex Gabor filter responses, modelling
receptive field properties in the visual cortex. While the camera
movements are computed with input images of coarse spatial
resolution, disparity calculation uses a finer resolution in the
scale space. The correspondence problem is solved implicitly by
restricting the disparity range around zero disparity to the
filter kernel sizes (Panum's area in the human visual system).
The vergence process is interpreted as a mechanism to minimize
global disparity, thereby setting a 3D region of interest for
subsequent disparity detection. The disparity map represents
smaller local disparities as an important cue for depth
perception. Experimental data for vergence in natural scenes and
resulting disparity maps are presented
Thesaurus image reconstruction; stereo image processing
Other Terms depth reconstruction; stereo camera system; dense disparity maps
; Gabor filter responses; visual cortex; disparity calculation;
correspondence problem; disparity range; global disparity;
natural scenes
ClassCodes C5260B; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4778274
AbstractNos. C9411-5260B-195
ISBN or SBN 2 906899 95 X
References 12
Country Pub. France
date 1219
------------------------------------------------------------
Author Falzon, F.; Giraudon, G.;
INRIA, Sophia-Antipolis, France
Title Singularity analysis and derivative scale-space
Source Proceedings of IEEE Conference on Computer Vision and Pattern
Recognition; Part: Seattle, WA, USA; Part: 21-23 June 1994;
Sponsored by: IEEE Comput. Soc. Tech. Committee on Pattern Anal.
& Machine Intelligence;
Proceedings 1994 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.94CH3405-8);
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xvi+1009;
1994; pp. 245-50
Abstract The scale-space representations and wavelet transform theory have
provided us with good singularity detection frameworks. Thanks to
such methods, image understanding processes have become more and
more powerful. Some computer vision tasks also require a
knowledge on the nature of detected singularities. We propose, in
this paper, to take into account these requirements, and we
present a singularity detection method based on fractional
calculus arguments
Thesaurus computer vision; wavelet transforms
Other Terms scale-space representations; wavelet transform; singularity
detection; image understanding; computer vision; fractional
calculus
ClassCodes C1250; C5260B; C1130
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4777938
AbstractNos. C9411-1250-133
ISBN or SBN 0 8186 5825 8
References 26
U.S. Copyright Clearance Center Code
1063-6919/94/$3.00
Country Pub. USA
date 1228
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Author Matsopoulos, G.; Marshall, S.;
Strathclyde Univ., Glasgow, UK
Title Feature migration in morphological scale space
Source Proceedings of ICASSP '93; Part: Minneapolis, MN, USA; Part: 27-
30 April 1993;
Sponsored by: IEEE Signal Process. Soc;
ICASSP-93. 1993 IEEE International Conference on Acoustics,
Speech, and Signal Processing (Cat. No.92CH3252-4);
New York, NY, USA;
IEEE;
5 vol. (652+735+606+559+681);
1993; pp. 599-602 vol.3
Abstract A novel morphological operator for scale space evaluation is
introduced. The operator (X/sub B/)/sup B/ is less prone to
object shrinkage and signal spreading than the Gaussian approach,
and it treats similarly the intrusions and protrusions of the
original image. Zero crossing migration with respect to this
operation for various types of signal is derived. In order to
track events efficiently from scale to scale, it is necessary to
understand how the zero crossings of a signal migrate with the
scale factor. It is shown that equations can be produced to
describe this movement for specific special cases, such as ramp
and edges. The new theoretical results can be used to make
feature tracking with nonlinear techniques more efficient
Thesaurus feature extraction; image processing; mathematical morphology;
tracking
Other Terms morphological operator; scale space evaluation; object shrinkage
; signal spreading; zero crossings; feature tracking;
nonlinear techniques
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4777723
AbstractNos. B9411-6140C-204; C9411-1250-123
ISBN or SBN 0 7803 0946 4
References 5
U.S. Copyright Clearance Center Code
0 7803 0946 4/93/$3.00
Country Pub. USA
date 1213
------------------------------------------------------------
Author Ogniewicz, R.L.;
Commun. Technol. Lab., Swiss Federal Inst. of Technol., Zurich,
Switzerland
Title Skeleton-space: a multiscale shape description combining region
and boundary information
Source Proceedings of IEEE Conference on Computer Vision and Pattern
Recognition; Part: Seattle, WA, USA; Part: 21-23 June 1994;
Sponsored by: IEEE Comput. Soc. Tech. Committee on Pattern Anal.
& Machine Intelligence;
Proceedings 1994 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.94CH3405-8);
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xvi+1009;
1994; pp. 746-51
Abstract A multiscale extension to the medial axis transform(MAT) or
skeleton can be obtained by combining information derived from a
scale-space hierarchy of boundary representations with region
information provided by the MAT. The skeleton-space is
constructed by attributing each skeleton component with a
hierarchically ordered sequence of residual values, each
expressing the saliency of the component at a distinct resolution
level. Since our method amounts to a rather symbolic than iconic
computation of a multiscale MAT, it does not introduce the
correspondence problem between distinct levels of detail, in
contrast to other commonly proposed techniques. Our multiscale
MAT is capable of describing complex shapes characterized by
significantly jagged boundaries. Furthermore, tracking the
evolution of prominent loci of the MAT such as nodes across
scales permits to assess the most significant skeleton
constituents and to automatically determine pruning parameters. A
salient subset of the MAT (first order skeleton) can be extracted
without the need of manual threshold adjustment
Thesaurus image processing; mathematical morphology
Other Terms skeleton-space; multiscale shape description; boundary
information; region information; medial axis transform; scale-
space hierarchy; boundary representations; hierarchically
ordered sequence; pruning parameters; image analysis;
mathematical morphology
ClassCodes B6140C; C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4771239
AbstractNos. B9411-6140C-098; C9411-1250-080
ISBN or SBN 0 8186 5825 8
References 16
U.S. Copyright Clearance Center Code
1063-6919/94/$3.00
Country Pub. USA
date 1228
------------------------------------------------------------
Author Goshtasby, A.; O'Neill, W.D.;
Dept. of Electr. Eng. & Comput. Sci., Chicago Univ., IL, USA
Title Curve fitting by a sum of Gaussians
Source CVGIP: Graphical Models and Image Processing;
CVGIP, Graph. Models Image Process. (USA);
vol.56, no.4;
July 1994; pp. 281-8
Abstract Gaussians are useful in multiscale representation of video data.
An algorithm is presented which approximates a sequence of
uniformly spaced single-valued data by a sum of Gaussians with a
prescribed accuracy. The scale-space image of the data is used to
estimate the number of Gaussians and their initial parameters.
The Marquardt algorithm (1963) is then used to optimize the
parameters
Thesaurus curve fitting; image processing; optimisation; parameter
estimation
Other Terms curve fitting; Gaussians; multiscale representation; video data
; Marquardt algorithm; initial parameters; scale-space image
ClassCodes C5260B; C1250; C1180; C6130B
Article Type Theoretical / Mathematical
Coden CGMPE5
Language English
RecordType Journal
ControlNo. 4769682
AbstractNos. C9411-5260B-027
ISSN 10499652
References 8
U.S. Copyright Clearance Center Code
1049-9652/94/$6.00
Country Pub. USA
date 1229
------------------------------------------------------------
Author Tremblay, M.; Savard, M.; Poussart, D.;
Dept. of Electr. Eng., Laval Univ., Que., Canada
Title Medium level scene representation using a VLSI smart hexagonal
sensor with multiresolution edge extraction capability and scale
space integration processing
Source Proceedings of IEEE Conference on Computer Vision and Pattern
Recognition; Part: Seattle, WA, USA; Part: 21-23 June 1994;
Sponsored by: IEEE Comput. Soc. Tech. Committee on Pattern Anal.
& Machine Intelligence;
Proceedings 1994 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.94CH3405-8);
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xvi+1009;
1994; pp. 632-7
Abstract This paper presents a sensing approach where photo-transduction,
multi-resolution feature extraction, scale-space integration and
edge tracking are performed on a mixed (digital-analog) VLSI
architecture in order to generate medium-level scene description.
The proposed system is mainly targeted for robot vision
applications where feature description is preferred to a set of
raw or raster 2D images and edge maps. The Multiport Access photo-
Receptor (MAR) is a CMOS sensor and represents the main sensory
part of this integrated image acquisition system. VLSI also
provides means to integrate analog computing, digital controller
and DSP co-processor modules which define a powerful sensory chip
set for focal plane image processing. A current version of the
MAR sensor which implements 256*256 pixels includes 16 analog
spatial filters which simultaneously compute multiresolution edge
maps. This unique 2D hexagonal smart sensor approach which
performs up to 8.5*10/sup 9/ arithmetic Op/sec during the
acquisition/filtering phase and 25*10/sup 9/ Logical Op/sec for
scale-space integration allows high resolution image capability.
It represents a significant improvement for passive sensory units
in a compact assembly for computer vision applications
Thesaurus CMOS integrated circuits; computer vision; edge detection;
feature extraction; image sensors; spatial filters; VLSI
Other Terms medium level scene representation; VLSI smart hexagonal sensor;
multiresolution edge extraction capability; scale space
integration processing; feature extraction; edge tracking;
mixed digital-analog VLSI architecture; robot vision; Multiport
Access photo-Receptor; CMOS sensor; image acquisition system;
digital controller; DSP co-processor modules; focal plane image
processing; analog spatial filters; multiresolution edge maps
ClassCodes A4280Q; B7230G; B6140C; B2570D; C1250; C5260B; C3240K
Article Type Applications; Practical
Language English
RecordType Conference
ControlNo. 4764238
AbstractNos. A9420-4280Q-004; B9410-7230G-033; C9410-1250-212
ISBN or SBN 0 8186 5825 8
References 12
U.S. Copyright Clearance Center Code
1063-6919/94/$3.00
Country Pub. USA
date 1228
------------------------------------------------------------
Author Jang, B.K.;
Health Sci. Res. Lab., Eastman Kodak Co., Rochester, NY, USA
Title Morphological scale space for shape smoothing
Source Proceedings of the Fourth International Conference on Signal
Processing Applications and Technology. ICSPAT '93; Part: vol.1;
Part: Santa Clara, CA, USA; Part: 28 Sept.-1 Oct. 1993;
Proceedings of the Fourth International Conference on Signal
Processing Applications and Technology;
Newton, MA, USA;
DSP Associates;
2 vol. 1675;
1993; pp. 746-55 vol.1
Abstract In this paper, we describe a multiscale image representation
based on morphological operations. A set of boundaries of an
object is first smoothed by a number of opening and closing
operations each using a different size structuring element,
generating the multiple scale representation. Then, depending on
specific applications, features of the smoothed boundary are
extracted and linked together across a continuum of scales
forming a map called the morphological scale space (MSS).
Properties of this scale space map are investigated. A shape
smoothing algorithm is presented to show how the scale space
representation along with an organization scheme could be applied
to solve some practical vision problems. Specifically, in line
with Witkin's idea of Gaussian scale space filtering, the
organization scheme is developed to determine the relationship
among various boundary features. As a consequence, the proposed
algorithm allows the selection of the perceptually dominant
scales for shape smoothing without prior knowledge of the object
boundary and its noise. The proposed algorithm uses both region
and boundary information, addresses the issues of local and
global information, and solves the problems of scale. Moreover,
the method is computationally efficient, parameter free, and
stable
Thesaurus computer vision; feature extraction; mathematical morphology
Other Terms morphological scale space; shape smoothing; multiscale image
representation; closing operations; opening operations;
structuring element; smoothed boundary; feature extraction;
scale space map; practical vision problems; Gaussian scale
space filtering; boundary features; perceptually dominant scales
ClassCodes B6140C; C1250; C5260B
Article Type Practical; Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4759476
AbstractNos. B9410-6140C-309; C9410-1250-171
References 12
Country Pub. USA
date 1218
------------------------------------------------------------
Author Jones, A.G.; Taylor, C.J.;
Dept. of Med. Biophys., Manchester Univ., UK
Title Robust shape from shading
Source Image and Vision Computing;
Image Vis. Comput. (UK);
vol.12, no.7;
Sept. 1994; pp. 411-21
Abstract Existing shape from shading algorithms are not robust enough to
work reliably with real images. We present a new paradigm for
shape from shading based upon a scale space surface
representation. Using this representation, the shape from shading
problem becomes one of forming a surface from Gaussian basis
functions in such a way that the shading in the original image is
explained. The algorithm is extremely robust, producing
convincing results even when there is considerable noise present.
In its current form, the algorithm requires the reflectance
function to be approximately circularly symmetric. We show
results for synthetic images, both with and without added noise,
and for real scanning electron microscope images
Thesaurus computer vision; image recognition; noise
Other Terms algorithms; real images; scale space surface representation;
robust shape from shading; surface; Gaussian basis functions;
noise; reflectance function; synthetic images; scanning
electron microscope images
ClassCodes C5260B
Article Type Practical
Coden IVCODK
Language English
RecordType Journal
ControlNo. 4756038
AbstractNos. C9410-5260B-157
ISSN 02628856
References 15
U.S. Copyright Clearance Center Code
0262-8856/94/07/0411-11$10.00
Country Pub. UK
date 1231
------------------------------------------------------------
Author Kulkarni, A.; Shevgaonkar, R.; Sahasrabudhe, S.C.;
Dept. of Electr. Eng., Indian Inst. of Technol., Bombay, India
Title Edge detection using scale space knowledge
Source Proceedings of TENCON '93. IEEE Region 10 International
Conference on Computers, Communications and Automation; Part:
vol.2; Part: Beijing, China; Part: 19-21 Oct. 1993;
Proceedings TENCON '93. 1993 IEEE Region 10 Conference on
'Computer, Communication, Control and Power Engineering' (Cat. No.
93CH3286-2);
New York, NY, USA;
IEEE;
5 vol. (xxvi+1206+xvii+676+xv+580+xvii+619);
1993; pp. 986-90 vol.2
Editor Yuan Baozong
Abstract Edge detection has acquired enormous importance in computer
vision research: gaussian filter has been widely used in the past
to accomplish this task. Although the gaussian filter has nice
scaling behaviour and is computationally elegant, it suffers from
the disadvantage of delocalisation of edges when operated at
higher scales. Multi-scale processing of an image is thus
required. In this paper, the process of edge detection has been
looked upon as a reasoning problem. In the past, knowledge
handling and reasoning have been attributed to high level vision
routines, but from the results presented here, it can be argued
that reasoning does play an important role in the process of edge
detection. The knowledge base required for this is formed out of
the theory of scale space. Particular emphasis is laid on the
behaviour of delocalised, missing and false or spurious edges in
the scale space. The scale space is formed by operating the LoG
filter of different sizes on the input image. The dissimilarity
among the zero crossings is measured across the scales. It is
useful in the removal of false edges. A compatibility measure
relates the zero-crossing contour with the current scale
parameter, sigma . The rules are coded in NEXPERT OBJECT 2.0. The
results are compared with Canny's multiple edge detection
algorithm (J.F. Canny, 1986)
Thesaurus computer vision; edge detection; inference mechanisms;
knowledge based systems
Other Terms edge detection; scale space knowledge; computer vision research;
gaussian filter; scaling behaviour; multi-scale processing;
image processing; reasoning problem; knowledge handling;
reasoning; knowledge based systems; spurious edges; LoG filter;
zero-crossing contour; NEXPERT OBJECT 2.0; multiple edge
detection algorithm
ClassCodes B6140C; C5260B; C6170
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4750929
AbstractNos. B9410-6140C-204; C9410-5260B-121
ISBN or SBN 0 7803 1233 3
References 16
Country Pub. USA
date 1219
------------------------------------------------------------
Author Fermuller, C.; Kropatsch, W.;
Comput. Vision Lab., Maryland Univ., College Park, MD, USA
Title A syntactic approach to scale-space-based corner description
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.16, no.7;
July 1994; pp. 748-51
Abstract Planar curves are described by information about corners
integrated over various levels of resolution. The detection of
corners takes place on a digital representation. To compensate
for ambiguities arising from sampling problems due to the
discreteness, results about the local behavior of curvature
extrema in continuous scale-space are employed
Thesaurus edge detection; image processing; parallel processing
Other Terms syntactic approach; scale space based corner description;
planar curves; resolution; corner detection; sampling problems;
curvature extrema
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4742145
AbstractNos. B9410-6140C-083; C9410-1250-056
ISSN 01628828
References 23
U.S. Copyright Clearance Center Code
0162-8828/94/$04.00
Country Pub. USA
date 1229
------------------------------------------------------------
Author Jianqing Liu; Yee-Hong Yang;
Comput. Vision Lab., Saskatchewan Univ., Saskatoon, Sask., Canada
Title Multiresolution color image segmentation
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.16, no.7;
July 1994; pp. 689-700
Abstract Image segmentation is the process by which an original image is
partitioned into some homogeneous regions. In this paper, a novel
multiresolution color image segmentation (MCIS) algorithm which
uses Markov random fields (MRF's) is proposed. The proposed
approach is a relaxation process that converges to the MAP
(maximum a posteriori) estimate of the segmentation. The quadtree
structure is used to implement the multiresolution framework, and
the simulated annealing technique is employed to control the
splitting and merging of nodes so as to minimize an energy
function and therefore, maximize the MAP estimate. The
multiresolution scheme enables the use of different dissimilarity
measures at different resolution levels. Consequently, the
proposed algorithm is noise resistant. Since the global
clustering information of the image is required in the proposed
approach, the scale space filter (SSF) is employed as the first
step. The multiresolution approach is used to refine the
segmentation. Experimental results of both the synthesized and
real images are very encouraging. In order to evaluate
experimental results of both synthesized images and real images
quantitatively, a new evaluation criterion is proposed and
developed
Thesaurus image segmentation; Markov processes; simulated annealing;
tree data structures
Other Terms multiresolution color image segmentation; Markov random fields;
relaxation process; maximum a posteriori estimate; quadtree
structure; simulated annealing; splitting; merging;
dissimilarity measures; noise resistant; global clustering
information; scale space filter; real images; synthesized
images; evaluation criterion
ClassCodes B6140C; B0260; B0240Z; C1250; C5260B; C1180; C1140Z
Article Type Practical; Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4742138
AbstractNos. B9410-6140C-078; C9410-1250-051
ISSN 01628828
References 19
U.S. Copyright Clearance Center Code
0162-8828/94/$04.00
Country Pub. USA
date 1229
------------------------------------------------------------
Author Pizer, S.M.; Burbeck, C.A.; Coggins, J.M.; Fritsch, D.S.; Morse,
B.S.;
Medical Image Display Res. Group, North Carolina Univ., Chapel
Hill, NC, USA
Title Object shape before boundary shape: scale-space medial axes
Source Journal of Mathematical Imaging and Vision;
J. Math. Imaging Vis. (Netherlands);
vol.4, no.3;
July 1994; pp. 303-13
Abstract Representing object shape in two or three dimensions has
typically involved the description of the object boundary. This
paper proposes a means for characterizing object structure and
shape that avoids the need to find an explicit boundary. Rather,
it operates directly from the image-intensity distribution in the
object and its background, using operators that respond to
"boundariness." It produces a sort of medial-axis description
that recognizes that both axis location and object width must be
defined according to a tolerance proportional to the object width.
This generalized axis is called the multiscale medial axis
because it is defined as a curve or set of curves in scale space.
It has all of the advantages of the traditional medial axis. It
also has significant new advantages: it does not require a
predetermination of exactly what locations are included in the
object, it provides gross descriptions that are stable against
image detail, and it can be used to identify subobjects and
regions of boundary detail and to characterize their shape
properties
Thesaurus edge detection; image processing
Other Terms boundary shape; scale space medial axes; object boundary;
object structure; object shape; image intensity distribution;
medial axis description; multiscale medial axis; image analysis;
shape description
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden JIMVEC
Language English
RecordType Journal
ControlNo. 4739197
AbstractNos. B9410-6140C-034; C9410-1250-023
ISSN 09249907
References 26
U.S. Copyright Clearance Center Code
0924-9907/94/$5.00
Country Pub. Netherlands
date 1229
------------------------------------------------------------
Author Yoon, S.H.; Alexander, W.E.; Kim, J.H.;
Dept. of Electr. & Comput. Eng., North Carolina State Univ.,
Raleigh, NC, USA
Title Scale-invariant shape representation based on the wavelet
transform
Source Signal Processing, Sensor Fusion, and Target Recognition III; Part
: Orlando, FL, USA; Part: 4-6 April 1994;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2232;
1994; pp. 142-53
Abstract Matching of occluded objects is a difficult problem. Moreover,
the problem is more difficult when scale-invariant matching is
needed. A scale invariant representation is essential for this
application. In this paper, we propose using the wavelet
transform of a boundary to obtain a scale-invariant
representation. We use the cubic B-spline as a smoothing function
of the wavelet transform since the B-spline is analytically well
defined and simple to implement. We implement the fast continuous
wavelet transform by using a dyadic wavelet decomposition and
dilated B-splines. As a result of using the wavelet transform, we
obtain boundaries at various scales while using a small number of
data points. The existing scale-space image approaches are not
effective for occluded object matching since they use a
normalized x-axis and too many data points. We propose a new
scale-invariant representation similar to the scale-space image.
The representation is generated by locating zero-crossings of the
curvature function of boundaries at only the scales where the
number of zero-crossings is changing. We scale the x-axis for
each scale instead of using the same normalization for all scales.
The proposed representation is scale-invariant and appropriate
for scale-invariant matching with occlusion
Thesaurus image recognition; invariance; splines (mathematics); wavelet
transforms
Other Terms scale-invariant shape representation; dyadic wavelet
decomposition; occluded objects; scale-invariant matching;
cubic B-spline; smoothing function; fast continuous wavelet
transform; dilated B-splines; scale-space image approaches;
curvature function
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4737080
AbstractNos. B9410-6140C-007; C9410-1250-005
ISSN 0277786X
References 21
U.S. Copyright Clearance Center Code
0 8194 1536 7/94/$6.00
Country Pub. USA
date 1226
------------------------------------------------------------
Author ter Haar Romeny, B.M.; Florack, L.M.J.; Salden, A.H.; Viergever,
M.A.;
3D Comput. Vision Res. Group, Utrecht Univ. Hospital, Netherlands
Title Higher order differential structure of images
Source Image and Vision Computing;
Image Vis. Comput. (UK);
vol.12, no.6;
July-Aug. 1994; pp. 317-25
Abstract This paper is meant as a tutorial on the basic concepts for
vision in the 'Koenderink' school. The concept of scale-space is
a necessity, if the extraction of structure from measured
physical signals (i.e. images) is at stage. The Gaussian
derivative kernels for physical signals are then the natural
analogues of the mathematical differential operators. This paper
discusses some interesting properties of the Gaussian derivative
kernels, like their orthogonality and behaviour with noisy input
data. Geometrical structure to extract is expressed in terms of
differential invariants, in this paper limited to invariants
under orthogonal transformations. Three representations are
summarized: cartesian, gauge and manifest invariant notation.
Many explicit examples are given. A section is included about the
computer implementation of the calculation of higher order
invariant structure
Thesaurus computer vision; feature extraction
Other Terms higher order differential image structure; measured physical
signals; Gaussian derivative kernels; mathematical differential
operators; manifest invariant notation; computer implementation;
higher order invariant structure
ClassCodes B6140C; C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Coden IVCODK
Language English
RecordType Journal
ControlNo. 4727494
AbstractNos. B9409-6140C-246; C9409-1250-155
ISSN 02628856
References 36
U.S. Copyright Clearance Center Code
0262-8856/94/06/0317-09$10.00
Country Pub. UK
date 1229
------------------------------------------------------------
Author Worring, M.; Smeulders, A.W.M.;
Dept. of Math. & Comput. Sci., Amsterdam Univ., Netherlands
Title Shape of an arbitrary finite point set in IR/sup 2/
Source Journal of Mathematical Imaging and Vision;
J. Math. Imaging Vis. (Netherlands);
vol.4, no.2;
May 1994; pp. 151-70
Abstract Studies the shape of a finite point set in IR/sup 2/, where the
points are not bound to a regular grid like Z/sup 2/. The shape
of a connected point set in IR/sup 2/ is captured by its boundary.
For a finite point set the boundary is a directed graph that
connects points identified as boundary points. The authors argue
that to serve as a proper boundary definition the directed graph
should regulate scale, be minimal, have an increasing interior
and be consistent with the boundary definition of connected
objects. The authors propose to use the directed variant of the
alpha -shape as defined by Edelsbrunner et al. (1983), which the
authors call the alpha -graph. The alpha -graph is based on a
generalization of the convex hull. The computational aspects of
the alpha -graph have been extensively studied, but little
attention has been paid to the potential use of the alpha -graph
as a shape descriptor or a boundary definition. In this paper the
authors prove that the alpha -graph satisfies the aforementioned
criteria. The authors also prove a relation between the alpha -
graph and the opening scale space from mathematical morphology.
In fact, the alpha -hull provides a generalization of this scale
space
Thesaurus computational geometry; directed graphs; image processing;
mathematical morphology
Other Terms arbitrary finite point set; IR/sup 2/; connected point set;
directed graph; boundary definition; alpha -shape; alpha -
graph; convex hull; shape descriptor; mathematical morphology
ClassCodes B6140C; B0250; C1250; C1160; C5260B
Article Type Practical; Theoretical / Mathematical
Coden JIMVEC
Language English
RecordType Journal
ControlNo. 4724559
AbstractNos. B9409-6140C-218; C9409-1250-133
ISSN 09249907
References 16
U.S. Copyright Clearance Center Code
0924-9907/94/$5.00
Country Pub. Netherlands
date 1227
------------------------------------------------------------
Author El-Fallah, A.I.; Ford, G.E.;
CIPIC, California Univ., Davis, CA, USA
Title Nonlinear adaptive image filtering based on inhomogeneous
diffusion and differential geometry
Source Image and Video Processing II; Part: San Jose, CA, USA; Part: 7-
9 Feb. 1994;
Sponsored by: SPIE; IS&T;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2182;
1994; pp. 49-63
Abstract The inadequacy of the classic linear approach to edge detection
and scale space filtering lies in the spatial averaging of the
Laplacian. The Laplacian is the divergence of the gradient and
thus is the divergence of both magnitude and direction. The
divergence in magnitude characterizes edges and this divergence
must not be averaged if the image structure is to be preserved.
We introduce a new nonlinear filtering theory that that only
averages the divergence of direction. This averaging keeps edges
and lines intact as their direction is nondivergent. Noise does
not have this nondivergent consistency and its divergent
direction will be averaged. Higher order structures such as
corners are singular points or inflection points in the
divergence of direction and also will be averaged. Corners are
intersection points of edges of nondivergent direction (or smooth
curves of small divergence in direction) and their averaging will
be limited. This approach provides a better compromise between
noise removal and preservation of image structure. Experiments
that verify and demonstrate the adequacy of this new theory are
presented
Thesaurus adaptive filters; differential geometry; edge detection;
filtering and prediction theory; noise
Other Terms nonlinear adaptive image filtering; inhomogeneous diffusion;
differential geometry; edge detection; scale space filtering;
nonlinear filtering theory; divergence of direction;
nondivergent consistency; corners; singular points; inflection
points; noise removal; image structure preservation; spatial
averaging
ClassCodes B6140C; C5260B; C1250
Article Type Theoretical / Mathematical; Experimental
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4716779
AbstractNos. B9409-6140C-077; C9409-5260B-054
ISSN 0277786X
References 16
U.S. Copyright Clearance Center Code
0 8194 1477 8/94/$6.00
Country Pub. USA
date 1224
------------------------------------------------------------
Author Peters, R.A., II; Nichols, J.A.;
Dept. of Electr. Eng., Vanderbilt Univ., Nashville, TN, USA
Title Morphological bandpass decomposition of images
Source Nonlinear Image Processing V; Part: San Jose, CA, USA; Part: 7-
9 Feb. 1994;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2180;
1994; pp. 163-74
Abstract The concept of a morphological size distribution is well known.
It can be envisioned as a sequence of progressively more highly
smoothed images which is a nonlinear analogue of scale space.
Whereas the differences between Gaussian lowpass filtered images
in scale space form a sequence of approximately Laplacian
bandpass filtered images, the difference image sequence from a
morphological size distribution is not bandpass in any usual
sense for most images. This paper presents a proof that a
strictly size band limited sequence can be created along one
dimension in an n dimensional image. This result is used to show
how an image time sequence can be decomposed into a set of
sequences each of which contains only events of a specific
limited duration. It is shown that this decomposition can be used
for noise reduction. This paper also presents two algorithms
which create from morphological size distributions, (pseudo) size
bandpass decompositions in more than one dimension. One algorithm
uses Vincent grayscale reconstruction on the size distribution.
The other reconstructs the difference image sequence
Thesaurus image reconstruction; image sequences; mathematical morphology;
random noise; statistical analysis
Other Terms morphological bandpass decomposition; morphological size
distribution; smoothed image sequences; scale space;
difference image sequence; band limited sequence; image time
sequence; noise reduction; bandpass decompositions; Vincent
grayscale reconstruction; size distribution
ClassCodes B6140C; C5260B
Article Type Theoretical / Mathematical; Experimental
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4716757
AbstractNos. B9409-6140C-057; C9409-5260B-037
ISSN 0277786X
References 8
U.S. Copyright Clearance Center Code
0 8194 1475 1/94/$6.00
Country Pub. USA
date 1224
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Author Bangham, J.A.;
Sch. of Inf. Syst., East Anglia Univ., Norwich, UK
Title Median and morphological scale space filtering and zero-crossings
Source Nonlinear Image Processing V; Part: San Jose, CA, USA; Part: 7-
9 Feb. 1994;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2180;
1994; pp. 90-8
Abstract This paper investigates nonlinear filter sequences (filters in
series, known as sieves) or banks (in parallel) as a means of
achieving multiscale decomposition. Recently multiscale
decomposition using both erosion (dilation) and closing (opening)
operations with sets of increasing scale flat structuring
elements have been used to analyse edges over multiple scales and
the granularity of images. These do not introduce new edges as
scale increases. However, they are not at all statistically
robust in the face of, for example, salt and pepper noise. This
paper shows that sieves also do not introduce new edges, are very
robust and perform at least as well as discreet Gaussian filters
when applied to sampled data. Analytical support for these
observations is provided by the morphology decomposition theorem
Thesaurus edge detection; filtering and prediction theory; mathematical
morphology; nonlinear systems
Other Terms morphological scale space filtering; median scale space filtering
; zero-crossings; multiscale decomposition; scale space
channels; nonlinear filter sequences; erosion operations;
dilation operations; closing operation; opening operations;
edge analysis; salt and pepper noise; sampled data; morphology
decomposition theorem
ClassCodes B6140C; C5260B; C1250
Article Type Experimental
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4716750
AbstractNos. B9409-6140C-051; C9409-5260B-030
ISSN 0277786X
References 15
U.S. Copyright Clearance Center Code
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Country Pub. USA
date 1224
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Author Miller, E.L.; Willsky, A.S.;
Lab. for Inf. & Decision Syst., MIT, Cambridge, MA, USA
Title Wavelet transforms and multiscale estimation techniques for the
solution of multisensor inverse problems
Source Wavelet Applications; Part: Orlando, FL, USA; Part: 5-8 April
1994;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2242;
1994; pp. 28-39
Abstract The application of multiscale and stochastic techniques to the
solution of linear inverse problems is presented. This approach
allows for the explicit and easy handling of a variety of
difficulties commonly associated with problems of this type.
Regularization is accomplished via the incorporation of prior
information in the form of a multiscale stochastic model. We
introduce the relative error covariance matrix (RECM) as a tool
for quantitatively evaluating the manner in which data
contributes to the structure of a reconstruction. In particular,
the use of a scale space formulation is ideally suited to the
fusion of data from several sensors with differing resolutions
and spatial coverage (e.g. sparse or limited availability).
Moreover, the RECM both provides us with an ideal tool for
understanding and analyzing the process of multisensor fusion and
allows us to define the space-varying optimal scale for
reconstruction as a function of the nature (resolution, quality,
and coverage) of the available data. Examples of our multiscale
maximum posteriori inversion algorithm are demonstrated using a
two channel deconvolution problem
Thesaurus estimation theory; inverse problems; matrix algebra; sensor
fusion; stochastic processes; wavelet transforms
Other Terms multiscale estimation techniques; multisensor inverse problems;
stochastic techniques; linear inverse problems; regularization;
multiscale stochastic model; relative error covariance matrix;
RECM; scale space formulation; data fusion; multisensor fusion;
space-varying optimal scale for reconstruction; multiscale
maximum posteriori inversion algorithm; channel deconvolution
problem
ClassCodes B6140; B0210; C1260; C1110
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4707528
AbstractNos. B9408-6140-144; C9408-1260-111
ISSN 0277786X
References 10
U.S. Copyright Clearance Center Code
0 8194 1546 4/94/$6.00
Country Pub. USA
date 1226
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Author Bala, J.W.; Wechsler, H.;
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Title Learning to detect targets using scale-space and genetic search
Source Proceedings of ICGA-93: Fifth International Conference on Genetic
Algorithms; Part: Urbana-Champaign, IL, USA; Part: 17-22 July
1993;
Proceedings of the Fifth International Conference on Genetic
Algorithms;
San Mateo, CA, USA;
Morgan Kaufmann;
xii+665;
1993; pp. 516-22
Editor Forrest, S.
Abstract Introduces a novel methodology for target detection using scale-
space and genetic algorithms (GAs). High-performance detection
operators, defined as 2D masks, are derived using GAs operating
at different levels of the Gaussian pyramid. The population of
operators, iteratively evaluated according to a statistical
performance index corresponding to target recognition ability,
evolves into an optimal set of scale-space masks using the
evolution principles of genetic search. Experimental results of
target detection in poor quality and noisy infrared images are
presented to illustrate the merit and feasibility of the proposed
method
Thesaurus genetic algorithms; image recognition; iterative methods;
learning (artificial intelligence); performance index; search
problems
Other Terms learning; scale-space image representation; high performance
detection operators; noisy IR images; iterative evaluation;
poor quality images; genetic search; target detection; genetic
algorithms; 2D masks; Gaussian pyramid; statistical
performance index; target recognition ability; evolution
ClassCodes C1250; C5260B; C1180; C1240
Article Type Practical; Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4706214
AbstractNos. C9408-1250-105
ISBN or SBN 1 558 60299 2
References 8
Country Pub. USA
date 1216
------------------------------------------------------------
Author De Graaf, C.N.; Koster, A.S.E.; Vincken, K.L.; Viergever, M.A.;
Comput. Vision Res. Group, Utrecht Univ., Netherlands
Title Validation of the interleaved pyramid for the segmentation of 3D
vector images
Source Pattern Recognition Letters;
Pattern Recognit. Lett. (Netherlands);
vol.15, no.5;
May 1994; pp. 469-75
Abstract A multiresolution pyramid with double scale space sampling
(compared to the Burt & Hong scheme, 1981) for the segmentation
of 3D images, of which the elements are multiple valued, is
described. Evaluation is carried out by quality constrained cost
analysis
Thesaurus image segmentation
Other Terms interleaved pyramid; 3D vector image segmentation;
multiresolution pyramid; double scale space sampling; multiple-
valued images; quality constrained cost analysis
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PRLEDG
Language English
RecordType Journal
ControlNo. 4697507
AbstractNos. B9408-6140C-054; C9408-1250-032
ISSN 01678655
References 10
U.S. Copyright Clearance Center Code
0167-8655/94/$07.00
Country Pub. Netherlands
date 1227
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Author Prasad, K.V.; Balaram, J.;
California Inst. of Technol., Pasadena, CA, USA
Title Automated inspection for remote telerobotic operations
Source Proceedings of 1993 IEEE International Conference on Robotics and
Automation; Part: Atlanta, GA, USA; Part: 2-6 May 1993;
Sponsored by: IEEE;
Proceedings IEEE International Conference on Robotics and
Automation (Cat. No.93CH3247-4);
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
3 vol. (xviii+1051+xvi+848+xviii+1042);
1993; pp. 883-8 vol.3
Abstract Automated inspection techniques being developed for surface
inspection of remote space platforms are reported. The unique
problems of performing visual telerobotic inspection in space are
identified. An image differencing method to detect changes to
surfaces over a period of time is presented, together with a
scale-space technique for flaw identification. Examples from
images of laboratory mockups of space platform modules are
presented to illustrate the results
Thesaurus aerospace control; automatic optical inspection; mobile robots;
space vehicles; telecontrol
Other Terms remote telerobotic operations; surface inspection; space
platforms; visual telerobotic inspection; image differencing
method; scale-space technique; flaw identification
ClassCodes C3360L; C3250; C3390
Article Type Applications; Practical
Language English
RecordType Conference
ControlNo. 4687369
AbstractNos. C9407-3360L-041
ISBN or SBN 0 8186 3450 2
References 9
U.S. Copyright Clearance Center Code
0 8186 3450 2/93/$3.00
Country Pub. USA
date 1214
------------------------------------------------------------
Author Brown, G.; Forte, P.; Malyan, R.; Barnwell, P.;
Mercury Commun., UK
Title Perceptual feature based object recognition for automatic
inspection
Source Machine Vision Applications, Architectures, and Systems
Integration II; Part: Boston, MA, USA; Part: 7-9 Sept. 1993;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2064;
1993; pp. 307-18
Abstract This paper describes the development of a practical object
recognition framework for industrial inspection applications. The
framework is being used to develop a prototype automatic
inspection system for surface mounted electronic assemblies. The
recognition technique uses the object oriented paradigm to both
process and model the image information. Three inter-linked
information structures, that allow both image and object
modelling information to be represented at multiple resolutions,
are described. The first structure is a hierarchical feature
based description constructed from the recursive grouping of
perceptual features. The second structure provides a containment
tree to describe the connections between sub-component parts of a
complex object. The final structure is the inheritance tree that
provides the capability to model multiple variations of the same
object type. The inspection module begins by processing image
information from a newly developed nonlinear shape abstraction
technique. The information is delivered in the form of a multi-
resolution scale space description of the captured image
Thesaurus assembling; automatic optical inspection; computer vision;
feature extraction; printed circuit manufacture; surface mount
technology
Other Terms perceptual feature based object recognition; automatic inspection
; industrial inspection; surface mounted electronic assemblies;
interlinked information structures; object modelling;
hierarchical feature based description; recursive grouping;
containment tree; image processing; inspection module;
nonlinear shape abstraction; multiresolution scale space
description
ClassCodes B0170L; B2210D; B6140C; C5260B; C1250; C3355F
Article Type Practical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4670634
AbstractNos. B9406-0170L-019; C9406-5260B-158
ISSN 0277786X
References 12
U.S. Copyright Clearance Center Code
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Country Pub. USA
date 1218
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------------------------------------------------------------
Author Bichsel, M.; Pentland, A.P.;
Media Lab., MIT, Cambridge, MA, USA
Title Human face recognition and the face image set's topology
Source CVGIP: Image Understanding;
CVGIP, Image Underst. (USA);
vol.59, no.2;
March 1994; pp. 254-61
Abstract Considering an n*n image as an n/sup 2/-dimensional vector, then
images of faces can be considered as points in this n/sup 2/-
dimensional image space. Previous studies of physical
transformations of the face, including translation, small
rotations, and illumination changes, showed that the set of face
images consists of relatively simple connected subregions in
image space. Consequently linear matching techniques can be used
to obtain reliable face recognition. However, for more general
transformations, such as large rotations or scale changes, the
face subregions become highly non-convex. We have therefore
developed a scale-space. matching technique that allows us to
take advantage of knowledge about important geometrical
transformations and about the topology of the face subregion in
image space. While recognition of faces is the focus of the paper,
the algorithm is sufficiently general to be applicable to a large
variety of object recognition tasks
Thesaurus face recognition; topology
Other Terms face recognition; face image; geometrical transformations;
topology; object recognition; physical transformations; small
rotations
ClassCodes C5260B; C1250; C1160
Article Type Theoretical / Mathematical
Coden CIUNEJ
Language English
RecordType Journal
ControlNo. 4668583
AbstractNos. C9406-5260B-137
ISSN 10499660
References 25
U.S. Copyright Clearance Center Code
1049-9660/94/$6.00
Country Pub. USA
date 1225
------------------------------------------------------------
Author Goshtasby, A.;
Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL,
USA
Title On edge focusing (scale-space imaging)
Source Image and Vision Computing;
Image Vis. Comput. (UK);
vol.12, no.4;
May 1994; pp. 247-56
Abstract An algorithm is described that can track edges determined by the
Laplacian of Gaussian operator from low to high resolution. The
algorithm does not require a precomputed scale step size, but
rather determines the step size adaptively by using the image
content. A binary search is carried out to find the topology of
the scale-space image, which is then used to track the edges. The
proposed algorithm guarantees correct edge tracking with step
sizes considerably larger than has been previously used
Thesaurus edge detection
Other Terms edge focusing; Gaussian operator; image content; binary search;
scale-space image
ClassCodes B6140C; C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Coden IVCODK
Language English
RecordType Journal
ControlNo. 4666552
AbstractNos. B9406-6140C-157; C9406-1250-111
ISSN 02628856
References 16
U.S. Copyright Clearance Center Code
0262-8856/94/040247-10$10.00
Country Pub. UK
date 1227
------------------------------------------------------------
Author Ray, B.K.; Ray, K.S.;
Electron. & Commun. Sci. Unit, Indian Stat. Inst., Calcutta, India
Title A new approach to scale-space image
Source Pattern Recognition Letters;
Pattern Recognit. Lett. (Netherlands);
vol.15, no.4;
April 1994; pp. 365-72
Abstract This paper presents a new approach to scale-space image based on
the authors' (1991) work on polygonal approximation. The
polygonal approximation involves a counter which can be varied to
produce different sets of vertex points and hence different
polygonal approximations. These polygons are combined to
construct a scale-space image. The scale-space image is in
conformity with the scale-space theory. The scale-space behaviour
of different corner models is also analysed and a method for
corner detection is proposed. The validity of the proposed
technique is tested through experimental results
Thesaurus edge detection; finite difference methods; image processing;
statistical analysis
Other Terms scale-space image; polygonal approximation; vertex points;
corner models; corner detection
ClassCodes B6140C; B0290P; B0240Z; C1250; C4170; C1140Z
Article Type Theoretical / Mathematical
Coden PRLEDG
Language English
RecordType Journal
ControlNo. 4666484
AbstractNos. B9406-6140C-151; C9406-1250-106
ISSN 01678655
References 9
U.S. Copyright Clearance Center Code
0167-8655/94/$07.00
Country Pub. Netherlands
date 1226
------------------------------------------------------------
Author Ter Haar Romeny, B.M.; Florack, L.M.J.; Salden, A.H.; Viergever,
M.A.;
3D Computer Vision Res. Group, Utrecht Univ. Hospital, Netherlands
Title Higher order differential structure of images
Source Proceedings of 13th International Conference on Information
Processing in Medical Imaging; Part: Flagstaff, AZ, USA; Part:
14-18 June 1993;
Information Processing in Medical Imaging. 13th International
Conference, IPMI '93 Proceedings;
Berlin, Germany;
Springer-Verlag;
xvi+567;
1993; pp. 77-93
Editor Barrett, H.H.; Gmitro, A.F.
Abstract Presents a tutorial on the basic concepts for vision in the
'Koenderink' school. The concept of scale-space is a necessity if
the extraction of structure from measured physical signals (i.e.
images) is being done. The Gaussian derivative kernels then are,
for physical signals, the natural analogs of the mathematical
differential operators. This paper discusses some interesting
properties of the Gaussian derivative kernels, like their
orthogonality and behaviour with noisy input data. Geometrical
structure to be extracted is expressed as differential invariants,
in this paper limited to invariants under orthogonal
transformations. Three representations are summarized: Cartesian,
gauge and manifest invariant notation. Many explicit examples are
given. A section is included about computer implementation of the
calculation of higher order invariant structure
Thesaurus computer vision; geometry; image processing
Other Terms higher order differential image structure; computer vision;
geometrical structure extraction; Cartesian representation;
gauge representation; scale-space; Gaussian derivative kernels;
orthogonality; noisy input data; manifest invariant notation;
higher order invariant structure
ClassCodes B6140C; C1250; C5260B
Article Type General or Review; Practical
Language English
RecordType Conference
ControlNo. 4648047
AbstractNos. B9405-6140C-252; C9405-1250-180
ISBN or SBN 3 540 56800 X
References 35
Country Pub. Germany
date 1215
------------------------------------------------------------
Author Brown, G.; Forte, P.; Malyan, R.;
Mercury Commun. Ltd., London, UK
Title Non-linear shape abstraction for automatic inspection
Source Vision Geometry II; Part: Boston, MA, USA; Part: 9-10 Sept. 1993
;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2060;
1993; pp. 125-32
Abstract The authors describe the implementation of a non-linear 2D shape
abstraction technique. The abstraction procedure systematically
simplifies the shape's description using a group of predefined
'rewrite rules'. This procedure operates on a new compact and
efficient two dimensional shape representation. The abstraction
technique generates a detailed scale space representation of the
shape being abstracted. The authors provide a method for
analysing this representation to determine the significant shape
descriptions. These significant descriptions are used to produce
a reduced scale space description of the shape, for use by an
object recognition module. The work described will form a module
in a system being developed at Kingston University, to inspect
surface mounted technology (SMT) circuit boards for defects.
These defects will include poor solder joint quality, component
placement faults, missing components, etc. The inspection system
uses images, captured from a CCD camera, which are initially
processed using a transputer. Early test results are presented to
show the benefits of this technique in comparison with Gaussian
smoothing
Thesaurus circuit analysis computing; computer vision; edge detection;
inspection; surface mount technology
Other Terms automatic inspection; non-linear 2D shape abstraction;
abstraction procedure; predefined rewrite rules; two
dimensional shape representation; scale space representation;
reduced scale space description; object recognition module;
surface mounted technology circuit boards; solder joint quality;
component placement faults; CCD camera; transputer
ClassCodes B1130B; C7410D; C5260B
Article Type Practical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4626930
AbstractNos. B9405-1130B-001; C9405-7410D-006
ISSN 0277786X
References 7
U.S. Copyright Clearance Center Code
0 8194 1325 9/93/$6.00
Country Pub. USA
date 1218
------------------------------------------------------------
Author Theimer, W.M.; Mallot, H.A.; Tolg, S.;
Inst. fur Neuroinf., Ruhr-Univ., Bochum, Germany
Title Phase method for binocular vergence control and depth
reconstruction
Source Intelligent Robots and Computer Vision XI: Biological, Neural Net
and 3-D Methods; Part: Boston, MA, USA; Part: 18-20 Nov. 1992;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1826;
1992; pp. 76-87
Abstract We present a technique to guide vergence movements for an active
stereo camera system and to construct dense disparity maps. Both
processes are described in the same theoretical framework based
on phase differences in complex Gabor filter responses, modelling
receptive field properties in the visual cortex. While the camera
movements are computed with coarse spatial resolution input
images, disparity calculation uses finer resolutions in a scale
space. The correspondence problem is solved implicitly by
restricting the disparity range around zero disparity to the
filter kernel sizes (Panum's area in the human visual system).
The method contrasts to matching algorithms-that require an
explicit search for correspondence-and to correlation, needing a
maximum detection in the correlation function. The vergence
process is interpreted as a mechanism to minimize global
disparity, thereby setting a 3D region of interest for subsequent
disparity detection. This small volume is centered around the
fixation point where both optical axes intersect. Additionally it
produces a scalar distance measure via vergence angles and camera
base. The disparity map represents smaller local disparities as
an important cue for depth perception. The vergence control works
in a real-time feedback loop. Quantitative results are presented
Thesaurus feedback; filtering and prediction theory; stereo image
processing
Other Terms phase method; binocular vergence control; depth reconstruction;
active stereo camera system; complex Gabor filter responses;
visual cortex; coarse spatial resolution input images; filter
kernel sizes; Panum's area; global disparity minimization;
fixation point; depth perception; real-time feedback loop
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4626626
AbstractNos. B9405-6140C-007; C9405-1250-008
ISSN 0277786X
References 13
U.S. Copyright Clearance Center Code
0 8194 1027 6/92/$4.00
Country Pub. USA
date 1207
------------------------------------------------------------
Author Chaney, R.D.;
Artificial Intelligence Lab., MIT, Cambridge, MA, USA
Title Computation of the medial axis skeleton at multiple complexities
Source Intelligent Robots and Computer Vision XI: Algorithms, Techniques
and Active Vision; Part: Boston, MA, USA; Part: 16-18 Nov. 1992;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1825;
1992; pp. 469-80
Abstract The medial axis skeleton is a thin line graph that preserves the
topology of a simply connected region. The skeleton has often
been cited as a useful representation for shape description,
region interpretation, and object recognition. Unfortunately, the
computation of the skeleton is extremely sensitive to variations
in the bounding contour. Tiny perturbations in the contour often
lead to spurious branches of the skeleton. In this paper, we
consider a robust method for computing the medial axis skeleton
across a variety of scales. The scale-space is parametric with
the complexity of the bounding contour. The complexity is defined
as the number of extrema of curvature in the contour. A set of
curves is computed to represent the bounding contour across a
variety of complexity measures. The curves possessing larger
complexity measures represent greater detail than curves with
smaller measures. A medial axis skeleton is computed directly
from each contour. The result is a set of skeletons that
represent only the gross structure of the region at coarse scales
(low complexity), but represent more of the detail at fine scales
(high complexity)
Thesaurus computational complexity; image processing; image recognition
Other Terms medial axis skeleton; multiple complexities; thin line graph;
topology; simply connected region; shape description; region
interpretation; object recognition; bounding contour variations;
scale-space; bounding contour
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4619983
AbstractNos. B9404-6140C-294; C9404-1250-184
ISSN 0277786X
References 11
U.S. Copyright Clearance Center Code
0 8194 1026 8/92/$4.00
Country Pub. USA
date 1207
------------------------------------------------------------
Author Johansen, P.;
Dept. of Comput. Sci., Copenhagen Univ., Denmark
Title On the classification of toppoints in scale space
Source Journal of Mathematical Imaging and Vision;
J. Math. Imaging Vis. (Netherlands);
vol.4, no.1;
Jan. 1994; pp. 57-67
Abstract An algebraic classification scheme for toppoints in scale space
is proposed. A critical point is a point whose spatial
derivatives are zero, and a toppoint is a critical point in which
the Hessian does not have full rank. A critical curve is a curve
consisting of critical points. It is proposed that toppoints be
classified according to the number of critical curves that
intersect at the toppoint. Toppoints are analyzed further when
one or two critical curves pass through the toppoint. Results on
extrema, saddle points and intersections are found
Thesaurus algebra; image recognition
Other Terms toppoint classification; scale space; algebraic classification
scheme; critical curves; extrema; saddle points; intersections
; image analysis
ClassCodes B6140C; B0210; C1250; C1110
Article Type Theoretical / Mathematical
Coden JIMVEC
Language English
RecordType Journal
ControlNo. 4616880
AbstractNos. B9404-6140C-247; C9404-1250-149
ISSN 09249907
References 12
U.S. Copyright Clearance Center Code
0924-9907/94/$5.00
Country Pub. Netherlands
date 1223
------------------------------------------------------------
Author Kelch, J.; Wein, B.;
Rogowski-Inst. for Electr. Eng., RWTH Aachen, Germany
Title Model based segmentation of the tongue surface using a modified
scale space filter
Source Visual Communications and Image Processing '93; Part: Cambridge,
MA, USA; Part: 8-11 Nov. 1993;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2094, pt.1;
1993; pp. 24-30
Abstract This edge detector is based on coarse-to-fine tracking by varying
the smoothing parameter of the Laplacian-of-Gaussian filter (LoG).
In this way contour segments of the tongue dorsum and other
objects are extracted. A model supports identification of the
tongue segments and interpolation of the surface in the
spatiotemporal space. The tongue is formed as a chain of
elliptical structure elements. This model stresses a direction to
detect the orientation of the tongue and is flexible enough to
form any shape. These structure elements are matched to the scale
segments by correlation. A trainable cost path classifier selects
the topological connections of the structure elements, which are
linked by a spline interpolation. Virtual three-dimensional views
of the contour surface in the spatiotemporal space are generated
with different azimuthal angles for visualization
Thesaurus biomedical ultrasonics; correlation methods; edge detection;
image segmentation; medical image processing; physiological
models; spatial filters; splines (mathematics); topology;
tracking
Other Terms model-based segmentation; ultrasonic imaging; modified scale
space filter; edge detector; coarse-to-fine tracking; tongue
segments; elliptical structure elements; trainable cost path
classifier; topological connections; spline interpolation;
visualization
ClassCodes A8760B; A4230V; A0260; B7510B; B7820; B6140C; B0290F; C7330
; C5260B; C4130
Article Type Applications; Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4614536
AbstractNos. A9408-8760B-003; B9404-7510B-029; C9404-7330-074
ISSN 0277786X
References 11
U.S. Copyright Clearance Center Code
0 8194 1369 0/93/$6.00
Country Pub. USA
date 1220
------------------------------------------------------------
------------------------------------------------------------
Author Alvarez, L.; Guichard, F.; Lions, P.-L.; Morel, J.-M.;
Dept. de Inf. y Sistemas, Las Palmas Univ., Spain
Title Axioms and fundamental equations of image processing
Source Archive for Rational Mechanics and Analysis;
Arch. Ration. Mech. Anal. (Germany);
vol.123, no.3;
1993; pp. 199-257
Abstract Image-processing transforms must satisfy a list of formal
requirements. We discuss these requirements and classify them
into three categories: 'architectural requirements' like locality,
recursivity and causality in the scale space, 'stability
requirements' like the comparison principle and 'morphological
requirements', which correspond to shape-preserving properties
(rotation invariance, scale invariance, etc.). A complete
classification is given of all image multiscale transforms
satisfying these requirements. This classification yields a
characterization of all classical models and includes new ones,
which all are partial differential equations. The new models we
introduce have more invariance properties than all the previously
known models and in particular have a projection invariance
essential for shape recognition. Numerical experiments are
presented and compared. The same method is applied to the
multiscale analysis of movies. By introducing a property of
Galilean invariance, we find a single multiscale morphological
model for movie analysis
Thesaurus image processing; partial differential equations; transforms
Other Terms image processing; transforms; architectural requirements;
locality; recursivity; causality; stability requirements;
comparison principle; morphological requirements; shape-
preserving properties; rotation invariance; scale invariance;
image multiscale transforms; partial differential equations;
movies; Galilean invariance; multiscale morphological model
ClassCodes B6140C; B0230; B0220; C1250; C4170
Article Type Theoretical / Mathematical
Coden AVRMAW
Language English
RecordType Journal
ControlNo. 4603142
AbstractNos. B9404-6140C-001; C9404-1250-001
ISSN 00039527
References 82
Country Pub. Germany
date 1210
------------------------------------------------------------
Author Ottenberg, K.; Neumann, H.; Stiehl, H.S.;
Philips GmbH Forschungslab., Hamburg, Germany
Title Quantitative description and reconstruction of intensity
functions using scale-space and multiresolution processing
Source Signal Processing VI - Theories and Applications. Proceedings of
EUSIPCO-92, Sixth European Signal Processing Conference; Part:
Brussels, Belgium; Part: 24-27 Aug. 1992;
Sponsored by: Belgian Nat. Fund for Sci. Res.; CERA; LMS Int;
Amsterdam, Netherlands;
Elsevier;
3 vol. lvii+1844;
1992; pp. 1425-8 vol. 3
Editor Vandewalle, J.; Boite, R.; Moonen, M.; Oosterlinck, A.
Abstract Differently scaled 1-D intensity discontinuities along the
gradient direction define significant image structure
intrinsically related to different physical causes in the scene,
e.g. step-edges in images due to cast shadow boundaries or
gradually changing edge profiles due to self shadow boundaries on
smoothly curved object surfaces. Reliable detection and
quantitative description of such a variety of scaled intensity
discontinuities (with a priori unknown relative contrasts, widths,
loci and orientations) in images require a family of
appropriately scaled operators and a generally applicable
quantitative multiscale processing scheme. Hence the authors
propose (i) a multiscale scheme following Marr's (1976) and
Korn's (1988) approach (ii) briefly present the theoretical
framework for the 1-D case, and (iii) briefly report on numerical
results from initial experiments with discrete 1-D data
Thesaurus image processing
Other Terms scale-space processing; image structure description; intensity
functions; multiresolution processing; 1-D intensity
discontinuities; gradient direction; image structure; edge
profiles; shadow boundaries; relative contrasts; widths; loci;
orientations; scaled operators; multiscale processing
ClassCodes B6140C
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4584721
AbstractNos. B9403-6140C-084
ISBN or SBN 0 444 89587 6
References 14
Country Pub. Netherlands
date 1204
------------------------------------------------------------
Author Laine, A.; Fan, J.;
Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA
Title Texture classification by wavelet packet signatures
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.15, no.11;
Nov. 1993; pp. 1186-91
Abstract This correspondence introduces a new approach to characterize
textures at multiple scales. The performance of wavelet packet
spaces are measured in terms of sensitivity and selectivity for
the classification of twenty-five natural textures. Both energy
and entropy metrics were computed for each wavelet packet and
incorporated into distinct scale space representations, where
each wavelet packet (channel) reflected a specific scale and
orientation sensitivity. Wavelet packet representations for
twenty-five natural textures were classified without error by a
simple two-layer network classifier. An analyzing function of
large regularity (D/sub 20/) was shown to be slightly more
efficient in representation and discrimination than a similar
function with fewer vanishing moments (D/sub 6/) In addition,
energy representations computed from the standard wavelet
decomposition alone (17 features) provided classification without
error for the twenty-five textures included in our study. The
reliability exhibited by texture signatures based on wavelet
packets analysis suggest that the multiresolution properties of
such transforms are beneficial for accomplishing segmentation,
classification and subtle discrimination of texture
Thesaurus feature extraction; feedforward neural nets; image recognition;
wavelet transforms
Other Terms texture classification; wavelet packet signatures; scale-
independence; wavelet packet spaces; sensitivity; selectivity;
energy metrics; entropy metrics; scale space representations;
scale sensitivity; orientation sensitivity; two-layer network
classifier
ClassCodes B6140C; C1250; C1230D
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4580750
AbstractNos. B9403-6140C-039; C9403-1250-028
ISSN 01628828
References 40
U.S. Copyright Clearance Center Code
0162-8828/93/$03.00
Country Pub. USA
date 1220
------------------------------------------------------------
Author Eggert, D.W.; Bowyer, K.W.; Dyer, C.R.; Christensen, H.I.;
Goldgof, D.B.;
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL,
USA
Title The scale space aspect graph
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.15, no.11;
Nov. 1993; pp. 1114-30
Abstract Currently the aspect graph is computed from the theoretical
standpoint of perfect resolution in object shape, the viewpoint
and the projected image. This means that the aspect graph may
include details that an observer could never see in practice.
Introducing the notion of scale into the aspect graph framework
provides a mechanism for selecting a level of detail that is
"large enough" to merit explicit representation. This effectively
allows control over the number of nodes retained in the aspect
graph. This paper introduces the concept of the scale space
aspect graph, defines three different interpretations of the
scale dimension, and presents a detailed example for a simple
class of objects, with scale defined in terms of the spatial
extent of features in the image
Thesaurus graph theory; image processing
Other Terms scale space aspect graph; projected image; scale dimension;
image processing
ClassCodes B6140C; B0250; C1250; C1160
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4580745
AbstractNos. B9403-6140C-036; C9403-1250-025
ISSN 01628828
References 39
U.S. Copyright Clearance Center Code
0162-8828/93/$03.00
Country Pub. USA
date 1220
------------------------------------------------------------
Author Lindeberg, T.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title Effective scale: a natural unit for measuring scale-space lifetime
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.15, no.10;
Oct. 1993; pp. 1068-74
Abstract A manner in which a notion of effective scale can be introduced
in a formal way is developed. For continuous signals, a scaling
argument directly gives a natural unit for measuring scale-space
lifetime in terms of the logarithm of the ordinary scale
parameter. That approach is, however, not appropriate for
discrete signals since an infinite lifetime would be assigned to
structures existing in the original signal. It is shown how such
an effective scale parameter can be defined to give consistent
results for both discrete and continuous signals. The treatment
is based on the assumption that the probability that a local
extremum disappears during a short-scale interval should not vary
with scale. As a tool for the analysis, estimates are given of
how the density of local extrema can be expected to vary with
scale in the scale-space representation of different random noise
signals both in the continuous and discrete cases
Thesaurus image processing
Other Terms effective scale; scale-space lifetime measurement unit
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4580739
AbstractNos. B9403-6140C-031; C9403-1250-020
ISSN 01628828
References 20
U.S. Copyright Clearance Center Code
0162-8828/93/$03.00
Country Pub. USA
date 1219
------------------------------------------------------------
Author Neumann, H.; Ottenberg, K.;
Hamburg Univ., Germany
Title Estimating ramp-edge attributes from scale-space
Source Signal Processing VI - Theories and Applications. Proceedings of
EUSIPCO-92, Sixth European Signal Processing Conference; Part:
Brussels, Belgium; Part: 24-27 Aug. 1992;
Sponsored by: Belgian Nat. Fund for Sci. Res.; CERA; LMS Int;
Amsterdam, Netherlands;
Elsevier;
3 vol. lvii+1844;
1992; pp. 603-6 vol.1
Editor Vandewalle, J.; Boite, R.; Moonen, M.; Oosterlinck, A.
Abstract Ramp-edges are frequently employed for modelling transitions of
the image intensity function between regions of constant
intensity value. For the domain of magnetic resonance images
(MRI), this type of 'discontinuity' model can explicitly be
derived from the underlying scene and the characteristics of the
measurement process (e.g. partial-volume effects). For an
automatic analysis of MRI, an estimation of the attributes
defining such a ramp-edge is essential. Other models for the
smooth image-transitions between plateaus corresponding to
different anatomical structures, generated by partial-volume
effects, within MRI have been investigated in detail by the
authors (1989, 1992). These models are based on step-edge models
convolved with Gaussian kernels, i.e. error-functions of
different variance. An analysis of the accuracy of regularized
first- and second-order differential operators for the
localization of discontinuities (including ramp-edges) has been
published by the authors (1990). The authors describe a procedure
to estimate the remaining attributes of a ramp-edge, the
transition width and the local contrast, from the scale-space
representation of the ramp-edge intensity function, generated by
the Gaussian convolution kernels
Thesaurus biomedical NMR; edge detection; medical image processing
Other Terms ramp-edge attributes estimation; image intensity function;
constant intensity value; magnetic resonance images; partial-
volume effects; MRI; step-edge models; Gaussian kernels;
error-functions; second-order differential operators;
transition width; local contrast; scale-space representation
ClassCodes A8760G; A8770E; B7510B; B6140C
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4576307
AbstractNos. A9404-8760G-029; B9402-7510B-137
ISBN or SBN 0 444 89587 6
References 0
Country Pub. Netherlands
date 1204
------------------------------------------------------------
Author Wong, Y.-F.;
Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA,
USA
Title Clustering data in the scale space
Source ICARCV '92. Second International Conference on Automation,
Robotics and Computer Vision; Part: Singapore; Part: 16-18 Sept.
1992;
Sponsored by: IEE; Inst. Meas.& Control; Econom. Development
Board; et al;
Singapore;
Nanyang Technol. Univ;
3 vol. (viii+934+viii+861+vii+908);
1992; pp. CV-20.2/1-5 vol.1
Abstract We derive a scale-space clustering algorithm based on information
theory and statistical mechanics. We introduce the concept of
cluster independence into clustering. The cluster centers
correspond to the local minima of a thermodynamical free energy,
which can be analyzed using nonlinear dynamics. The algorithm
works by melting the system to produce a tree of clusters in the
scale space. Melting can also handle variability in cluster
densities, cluster sizes and ellipsoidal shapes. We tested
successfully the algorithm on both simulated data and real data
Thesaurus dynamics; information theory; pattern recognition; statistical
mechanics
Other Terms data analysis; scale-space clustering algorithm; information
theory; statistical mechanics; local minima; thermodynamical
free energy; nonlinear dynamics
ClassCodes B6140C; B0240Z; B6110; C1250; C1140Z; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4575742
AbstractNos. B9402-6140C-283; C9402-1250-217
References 19
Country Pub. Singapore
date 1205
------------------------------------------------------------
Author Stach, J.; Shaw, S.;
SRI Int., Menlo Park, CA, USA
Title Robust relational trees by scale-space filtering
Source Proceedings of the IEEE-SP International Symposium Time-Frequency
and Time-Scale Analysis (Cat.No.92TH0478-8); Part: Victoria, BC,
Canada; Part: 4-6 Oct. 1992;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
577;
1992; pp. 173-6
Abstract A relational tree (RT) is a signal representation used to
discriminate between multidimensional signals with arbitrary
nonlinear monotonic distortion. The use of RTs is limited by
noise. Scale-space filtering takes advantage of the inherently
scale-like properties of an RT to provide a more robust signal
representation across distortions. Some methods and properties of
Gaussian scale-space filtering of RTs are examined. Scale trees
(STs) and conventionally filtered (fixed-scale) RTs have been
shown to be subsets of this process. Since the effect of scale-
space filtering is to move segmentation uncertainty toward the
leaves of the tree, other operations performed in the tree domain,
such as filtering, can be optimized as well
Thesaurus filtering and prediction theory; signal processing; trees
(mathematics)
Other Terms optimisation; Gaussian filtering; scale-space filtering;
relational tree; signal representation; multidimensional signals
; nonlinear monotonic distortion; noise; inherently scale-like
properties; segmentation uncertainty; leaves
ClassCodes B6140; B0250; C1260; C1160
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4575484
AbstractNos. B9402-6140-164; C9402-1260-127
ISBN or SBN 0 7803 0805 0
References 5
U.S. Copyright Clearance Center Code
0 7803 0805 0/92/$3.00
Country Pub. USA
date 1206
------------------------------------------------------------
Author Lindeberg, T.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title Discrete derivative approximations with scale-space properties: a
basis for low-level feature extraction
Source Journal of Mathematical Imaging and Vision;
J. Math. Imaging Vis. (Netherlands);
vol.3, no.4;
Nov. 1993; pp. 349-76
Abstract This article shows how discrete derivative approximations can be
defined so that scale-space properties hold exactly also in the
discrete domain. An axiomatic derivation of how a multiscale
representation of derivative approximations can be constructed
from a discrete signal, so that it possesses an algebraic
structure similar to that possessed by the derivatives of the
traditional scale-space representation in the continuous domain,
is given. A family of kernels is derived, that constitutes
discrete analogues to the continuous Gaussian derivatives. The
representation has theoretical advantages over other
discretizations of the scale-space theory in the sense that the
operators that commute before discretization also commute after
discretization. Some computational implications of this are that
derivative approximations can be computed directly from smoothed
data and that this will give exactly the same result as
convolution with the corresponding derivative approximation
kernel. Moreover, a number of normalization conditions are
automatically satisfied. The proposed methodology leads to a
scheme of computations of multiscale low-level feature extraction
that is conceptually very simple
Thesaurus computer vision; edge detection; feature extraction; filtering
and prediction theory; image recognition
Other Terms discrete derivative approximations; scale-space; low-level
feature extraction; axiomatic derivation; multiscale
representation; discrete signal; algebraic structure;
discretization; convolution; normalization conditions; edge
detection; compute vision
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Coden JIMVEC
Language English
RecordType Journal
ControlNo. 4557269
AbstractNos. B9402-6140C-024; C9402-1250-013
ISSN 09249907
References 36
U.S. Copyright Clearance Center Code
0924-9907/93/$5.00
Country Pub. Netherlands
date 1220
------------------------------------------------------------
Author Florack, L.M.J.; Ter Haar Romeny, B.M.; Koenderink, J.J.;
Viergever, M.A.;
Utrecht Univ., Netherlands
Title Cartesian differential invariants in scale-space
Source Journal of Mathematical Imaging and Vision;
J. Math. Imaging Vis. (Netherlands);
vol.3, no.4;
Nov. 1993; pp. 327-48
Abstract We present a formalism for studying local image structure in a
systematic, coordinate-independent, and robust way, based on
scale-space theory, tensor calculus, and the theory of invariants.
We concentrate on differential invariants. The formalism is of
general applicability to the analysis of grey-tone images of
various modalities, defined on a D-dimensional spatial domain. We
propose a "diagrammar" of differential invariants and tensors, i.
e., a diagrammatic representation of image derivatives in scale-
space together with a set of simple rules for representing
meaningful local image properties. All local image properties on
a given level of inner scale can be represented in terms of such
diagrams, and, vice versa, all diagrams represent coordinate-
independent combinations of image derivatives, i.e., true image
properties. We present complete and irreducible sets of
(nonpolynomial) differential invariants appropriate for the
description of local image structure up to any desired order. Any
differential invariant can be expressed in terms of polynomial
invariants, pictorially represented by closed diagrams. Here we
consider a complete, irreducible set of polynomial invariants up
to second order (inclusive)
Thesaurus image processing; invariance; tensors
Other Terms Cartesian differential invariants; scale-space; local image
structure; tensor calculus; grey-tone images; D-dimensional
spatial domain; diagrammar; image derivatives; true image
properties; polynomial invariants
ClassCodes B6140C; B0210; C1250; C1110
Article Type Theoretical / Mathematical
Coden JIMVEC
Language English
RecordType Journal
ControlNo. 4557268
AbstractNos. B9402-6140C-023; C9402-1250-012
ISSN 09249907
References 48
U.S. Copyright Clearance Center Code
0924-9907/93/$5.00
Country Pub. Netherlands
date 1220
------------------------------------------------------------
Author Snyder, W.E.; Youn-Sik Han; Bilbro, G.L.;
Dept. of Radiol., Med. Center Boulevard, Winston-Salem, NC, USA
Title A unified theory of edge-preserving smoothing
Source Artificial Neural Networks, 2. Proceedings of the 1992
International Conference (ICANN-92); Part: Brighton, UK; Part:
4-7 Sept. 1992;
Sponsored by: UK DTI; Eur. Commission;
Amsterdam, Netherlands;
Elsevier;
2 vol. (xviii+xxx+1700);
1992; pp. 1675-83 vol.2
Editor Aleksander, I.
Abstract Two edge-preserving smoothing techniques are discussed, mean
field annealing, graduated non-convexity, and compared to a
feature extraction technique known as variable conductance
diffusion. In previous literature, the first two techniques have
been shown to be equivalent. The third technique is shown to also
be equivalent. Furthermore, operations across scale space are
shown to be equivalent to annealing. The demonstration of the
mathematical equivalence of three independently derived and
successful methods leads to conclusions concerning the
fundamental nature of image analysis algorithms
Thesaurus feature extraction; image processing
Other Terms unified theory; edge-preserving smoothing techniques; mean
field annealing; graduated non-convexity; feature extraction
technique; variable conductance diffusion; mathematical
equivalence; image analysis algorithms
ClassCodes C5260B
Article Type Practical
Language English
RecordType Conference
ControlNo. 4553441
AbstractNos. C9401-5260B-232
ISBN or SBN 0 444 89488 8
References 26
Country Pub. Netherlands
date 1205
------------------------------------------------------------
Author Sapiro, G.; Tannenbaum, A.;
Technion-Israel Inst. of Technol., Haifa, Israel
Title Affine invariant scale-space
Source International Journal of Computer Vision;
Int. J. Comput. Vis. (Netherlands);
vol.11, no.1;
Aug. 1993; pp. 25-44
Abstract A new affine invariant scale-space for planar curves is presented.
The scale-space is obtained from the solution of a novel
nonlinear curve evolution equation which admits affine invariant
solutions. This flow was proved to be the affine analogue of the
well known Euclidean shortening flow. The evolution also
satisfies properties such as causality, which makes it useful in
defining a scale-space. Using an efficient numerical algorithm
for curve evolution, this continuous affine flow is implemented,
and examples are presented. The affine-invariant progressive
smoothing property of the evolution equation is demonstrated well
Thesaurus computational geometry
Other Terms affine invariant scale-space; planar curves; Euclidean
shortening flow; causality; progressive smoothing property
ClassCodes C4260
Article Type Bibliography/Literature Suvery; Practical; Theoretical /
Mathematical
Coden IJCVEQ
Language English
RecordType Journal
ControlNo. 4550660
AbstractNos. C9401-4260-066
ISSN 09205691
References 72
Country Pub. Netherlands
date 1217
------------------------------------------------------------
Author Lindberg, T.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title Detecting salient blob-like image structures and their scales
with a scale-space primal sketch: a method for focus-of-attention
Source International Journal of Computer Vision;
Int. J. Comput. Vis. (Netherlands);
vol.11, no.3;
Dec. 1993; pp. 283-318
Abstract Presents: (i) a multiscale representation of grey-level shape
called the scale-space primal sketch, which makes explicit both
features in scale-space and the relations between structures at
different scales, (ii) a methodology for extracting significant
blob-like image structures from this representation, and (iii)
applications to edge detection, histogram analysis, and junction
classification demonstrating how the proposed method can be used
for guiding later-stage visual processes. The representation
gives a qualitative description of image structure, which allows
for detection of stable scales and associated regions of interest
in a solely bottom-up data-driven way. In other words, it
generates coarse segmentation cues, and can hence be seen as
preceding further processing, which can then be properly tuned.
It is argued that once such information is available, many other
processing tasks can become much simpler. Experiments on real
imagery demonstrate that the proposed theory gives intuitive
results
Thesaurus computer vision; edge detection
Other Terms salient; scale-space primal sketch; multiscale representation;
grey-level shape; edge detection; histogram analysis; junction
classification; image structure; coarse segmentation; blob-like
ClassCodes C5260B; B6140C; C1250
Article Type Bibliography/Literature Suvery; Practical; Theoretical /
Mathematical
Coden IJCVEQ
Language English
RecordType Journal
ControlNo. 4544297
AbstractNos. B9401-6140C-236; C9401-5260B-142
ISSN 09205691
References 72
U.S. Copyright Clearance Center Code
0920-5691/93/$5.00
Country Pub. Netherlands
date 1221
------------------------------------------------------------
Author Taylor, J.R.; Olson, T.J.;
Dept. of Comput. Sci., Virginia Univ., Charlottesville, VA, USA
Title Precise vergence control in complex scenes
Source Proceedings of the SPIE - The International Society for Optical
Engineering;
Proc. SPIE - Int. Soc. Opt. Eng. (USA);
vol.2056;
1993; pp. 22-30
Abstract In binocular systems, vergence is the process of directing the
gaze so that the optical axes intersect at the point of interest.
Region based methods of disparity analysis provide fast and
reliable estimates of the vergence error, but it is difficult to
determine on what image features these approaches are in fact
verging. Previous approaches to vergence control have for the
most part failed to ensure that both cameras actually verge on
the object of interest, especially in complex scenes. This paper
presents a system that addresses this problem. By using the
cepstral filter in a multiresolution setting with a dominant
camera, the system can verge accurately in complex scenes.
Specifically, the system adaptively refines the vergence angle in
a scale space consisting of the center patches on a Gaussian
pyramid. The effects of the cepstrum in a multiresolution system
are analyzed, and the precision and performance of the new system
are verified on natural scenes
Thesaurus cameras; image processing; optical filters; optical
information processing; spectral analysis
Other Terms image processing; vergence control; complex scenes; optical
axes; cameras; cepstral filter; vergence angle; Gaussian
pyramid; cepstrum; multiresolution system
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Journal
ControlNo. 4542570
AbstractNos. B9401-6140C-197; C9401-1250-125
ISSN 0277786X
References 12
U.S. Copyright Clearance Center Code
0 8194 1321 6/93/$6.00
Country Pub. USA
date 1210
------------------------------------------------------------
Author Djemel Ziou; Tabbone, S.;
EERIE-LERI, Nimes, France
Title A multi-scale edge detector
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.26, no.9;
Sept. 1993; pp. 1305-14
Abstract A multi-scale edge detector with subpixel accuracy is described.
A subpixel Laplacian edge detector, recursively implemented, is
run at different scales and the recovered edge information is
combined. The multi-scale edge detection is based on the behavior
of edges in scale space and takes into account their physical
phenomena. With this purpose in mind, four step edge models are
considered: the ideal, the blurred, the pulse and the staircase.
It is emphasized that the use of two scales (the larger and the
smaller) is sufficient for good edge detection. Furthermore, a
set of rules is derived for combining edge information obtained
from a Laplacian detector which has some special properties.
However, this type of edge detector gives at least two classes of
false edges, one of which cannot be eliminated by the usual
thresholding methods. An appropriate thresholding algorithm is
given taking into account the origin of the false edges and their
behavior in scale space
Thesaurus edge detection
Other Terms multi-scale edge detector; subpixel accuracy; subpixel
Laplacian edge detector; scale space; step edge models;
thresholding algorithm; ideal model; blurred model; pulse model
; staircase model
ClassCodes C1250; B6140C; C5260B
Article Type Practical; Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 4528349
AbstractNos. B9401-6140C-048; C9401-1250-029
ISSN 00313203
References 24
U.S. Copyright Clearance Center Code
0031-3203/93/$6.00+.00
Country Pub. UK
date 1218
------------------------------------------------------------
Author Barth, E.; Zetzsche, C.; Ferraro, M.; Rentschler, I.;
Inst. fur Medizinische Psychol., Munchen, Germany
Title Fractal properties from 2D-curvature on multiple scales
Source Geometric Methods in Computer Vision II; Part: San Diego, CA, USA
; Part: 12-13 July 1993;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2031;
1993; pp. 87-99
Abstract Basic properties of 2D-nonlinear scale-space representations of
images are considered. Local-energy filters are used to estimate
the Hausdorff dimension, D/sub H/, of images. A new fractal
dimension, D/sub N/, defined as a property of 2D-curvature
representations on multiple scales, is introduced as a natural
extension of traditional fractal dimensions, and it is shown that
the two types of fractal dimensions can give a less ambiguous
description of fractal image structure. Some more general
properties of curvature representations on multiple scales are
considered. Simulations are used to analyse the stability of
curvature maxima across scale and to illustrate that spurious
resolution can be avoided by extraction of 2D-curvature features
Thesaurus computer vision; fractals; image processing
Other Terms Hausdorff dimension; 2D-curvature representations on multiple
scales; fractal dimensions; fractal image structure; stability;
spurious resolution
ClassCodes B6140C; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4514973
AbstractNos. B9312-6140C-162; C9312-5260B-106
ISSN 0277786X
References 25
U.S. Copyright Clearance Center Code
0 8194 1280 5/93/$6.00
Country Pub. USA
date 1216
------------------------------------------------------------
Author Salden, A.H.; ter Haar Romeny, B.M.; Viergever, M.A.;
3D Comput. Vision Res. Group, Utrecht Univ. Hospital, Netherlands
Title Affine and projective differential geometric invariants of space
curves
Source Geometric Methods in Computer Vision II; Part: San Diego, CA, USA
; Part: 12-13 July 1993;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2031;
1993; pp. 64-74
Abstract By means of classical scale space theory, algebraic invariance
theory and classical differential geometry a new method of shape
description for space curves from one or multiple views is
proposed in terms of complete and irreducible sets of invariants.
The method is based on defining implicitly connections for the
observed curves that are highly correlated to the projected space
curves, assumed to reveal themselves as coherent structures in
the scale space representation of the differential structure of
the input images. Several applications to stereo, optic flow,
texture analysis and image matching are indicated briefly
Thesaurus computer vision; curve fitting; differential geometry; image
texture; stereo image processing; surface fitting
Other Terms affine differential geometric invariants; projective
differential geometric invariants; scale space theory;
algebraic invariance theory; shape description; space curves;
coherent structures; stereo; optic flow; texture analysis;
image matching
ClassCodes B6140C; B0250; C5260B; C1160; C4260
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4514971
AbstractNos. B9312-6140C-160; C9312-5260B-104
ISSN 0277786X
References 28
U.S. Copyright Clearance Center Code
0 8194 1280 5/93/$6.00
Country Pub. USA
date 1216
------------------------------------------------------------
Author Chen, J.G.; Tian, Q.; Ren, X.H.;
Comput. Center, Taiyuan Univ. of Technol., Shanxi, China
Title Adaptive edge focusing
Source Communications on the Move. Singapore. ICCS/ISITA '92(Cat. No.
92TH0479-6); Part: Singapore; Part: 16-20 Nov. 1992;
Sponsored by: IEEE; Singapore Telecommn.; Telecommn.Authority
Singapore; et al;
New York, NY, USA;
IEEE;
3 vol. (xxvii+1422);
1990; pp. 624-32 vol.2
Editor Ng, C.S.; Yeo, T.S.; Yeo, S.P.
Abstract Edge focusing, an efficient implementation method of continuous
scale space filtering, has achieved better result in edge
detection. Yet, the edge focusing algorithm smooths all edges
with the filter of same scale, that generates ragged edges in the
following areas: (1) area with diffuse edge, (2) texture edges.
An optimal scale of edge detector is derived. With this optimal
scale, the original edge focusing algorithm is modified. During
the process of the revised edge focusing, if the scale of the
edge detector has reached the optimal scale at any edge point,
then the edge at that point will not be changed any more with a
decreasing scale of the filter. The benefit of this modification
is that it can avoid ragged edge and false edge points. The
performance of the modified edge focusing algorithm is better
than the original one. The experimental results support this
conclusion
Thesaurus edge detection
Other Terms adaptive edge focusing; continuous scale space filtering; edge
detection; edge focusing algorithm; diffuse edge; texture edges
; optimal scale
ClassCodes B6140C; C1250
Article Type Experimental
Language English
RecordType Conference
ControlNo. 4513283
AbstractNos. B9312-6140C-146; C9312-1250-116
ISBN or SBN 0 7803 0803 4
References 18
Country Pub. USA
date 1207
------------------------------------------------------------
Author Mori, K.; Matsuda, M.; Doi, S.; Takahashi, H.; Shimizu, E.;
Dept. of Electron., Osaka Electro-Commun. Univ., Japan
Title The real-time underwater data transmission system using scale-
space filtering
Source Parallel Computing and Transputer Applications; Part: Barcelona,
Spain; Part: 21-25 Sept. 1992;
Barcelona, Spain;
CIMNE;
2 vol. 1520;
1992; pp. 356-65 vol.1;
Available from: IOS Press, Amsterdam, Netherlands
Editor Valero, M.; Onate, E.; Jane, M.; Larriba, J.L.; Suarez, B.
Abstract The underwater data transmission using scale-space filtering and
fingerprint pattern keying as the data transmission method has
been proposed. The matching method using the number of the zero-
cross points in fingerprint pattern keying is proposed as one of
the data transmission methods which is conscious of the real-time
processing. The real-time underwater data transmission system
based on the parallel connected transputer array is designed
Thesaurus real-time systems; signal processing; transputer systems;
underwater sound
Other Terms real-time underwater data transmission; scale-space filtering;
fingerprint pattern keying; matching method; zero-cross points;
parallel connected transputer array
ClassCodes A4330; B6270; C5260; C5220P
Article Type Practical
Language English
RecordType Conference
ControlNo. 4508968
AbstractNos. A9323-4330-005; B9312-6270-001; C9312-5260-006
ISBN or SBN 84 87867 13 8
References 3
Country Pub. Spain
date 1205
------------------------------------------------------------
Author Campos, J.C.; Linney, A.D.; Moss, J.P.;
Univ. Coll., London, UK
Title The analysis of facial profiles using scale space techniques
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.26, no.6;
June 1993; pp. 819-24
Abstract A method is presented of analysing facial profiles by using scale
space techniques, reported in the pattern recognition literature.
Through this technique landmarks, which are some extremal points
on the profile are mathematically defined in order to divide the
profile into a number of regions considered suitable for analysis.
They are seen to correspond to parts of the face of interest to
the clinician. Thus, the whole profile can be qualitatively
described by the scale space image and the shape of individual
regions quantitatively described by a curvature value. A mid-line
facial profile is used to illustrate the method and a cleft
palate case is analysed and the assessment of changes due to
surgical correction are shown
Thesaurus face recognition; image segmentation
Other Terms image processing; profile segmentation; shape description;
Gaussian smoothing; zero crossings; facial profiles; scale
space techniques; pattern recognition; landmarks; curvature
value
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 4507623
AbstractNos. B9312-6140C-039; C9312-1250-032
ISSN 00313203
References 17
U.S. Copyright Clearance Center Code
0031-3203/93/$6.00+.00
Country Pub. UK
date 1215
------------------------------------------------------------
Author Wong, Y.; Posner, E.C.;
Lawrence Livermore Nat. Lab., CA, USA
Title A new clustering algorithm applicable to multispectral and
polarimetric SAR images
Source IEEE Transactions on Geoscience and Remote Sensing;
IEEE Trans. Geosci. Remote Sens. (USA);
vol.31, no.3;
May 1993; pp. 634-44
Abstract The authors applied a scale-space clustering algorithm to the
classification of a multispectral and polarimetric SAR image of
an agricultural site. After the initial polarimetric and
radiometric calibration and noise cancellation, a 12-dimensional
feature vector for each pixel was extracted from the scattering
matrix. The clustering algorithm partitioned a set of unlabeled
feature vectors from 13 selected sites, each site corresponding
to a distinct crop, into 13 clusters without any supervision. The
cluster parameters were then used to classify the whole image.
The classification map is much less noisy and more accurate than
those obtained by hierarchical rules. Starting with every point
as a cluster, the algorithm works by melting the system to
produce a tree of clusters in the scale space. It can cluster
data in any multidimensional space and its insensitive to
variability in cluster densities, sizes and ellipsoidal shapes.
This algorithm, more powerful than existing ones, may be useful
for remote sensing for land use
Thesaurus image recognition; remote sensing by radar
Other Terms multispectral SAR; synthetic aperture radar; clustering
algorithm; polarimetric SAR images; classification;
agricultural site; 12-dimensional feature vector; scattering
matrix; unlabeled feature vectors; crop; melting; tree of
clusters; scale space; multidimensional space; remote sensing;
land use
ClassCodes B7730; B6320; B6140C
Article Type Applications; Theoretical / Mathematical
Coden IGRSD2
Language English
RecordType Journal
ControlNo. 4505451
AbstractNos. B9312-7730-002
ISSN 01962892
References 26
U.S. Copyright Clearance Center Code
0196-2892/93/$03.00
Country Pub. USA
date 1214
------------------------------------------------------------
Author Roca, F.X.; Binefa, X.; Vitria, J.;
Dept. d'Inf., Univ. Autonoma de Barcelona, Spain
Title Multiscale structure extraction using morphological tools:
applications to edge detection
Source Image Algebra and Morphological Image Processing IV; Part: San
Diego, CA, USA; Part: 12-13 July 1993;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2030;
1993; pp. 231-9
Abstract The purpose of multiscale analysis is to extract information from
the original image features, studying their behaviour through
various scale levels. This paper presents a new methodology,
based on the use of tools provided by Mathematical Morphology,
applied to scale-space image feature tracing. This methodology is
here intended to solve two concrete problems: edge detection and
depth perception
Thesaurus edge detection; feature extraction; mathematical morphology
Other Terms image processing; structure extraction; morphological tools;
edge detection; multiscale analysis; methodology; scale-space
image feature tracing; depth perception
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4504571
AbstractNos. B9312-6140C-022; C9312-1250-016
ISSN 0277786X
References 17
U.S. Copyright Clearance Center Code
0 8194 1279 1/93/$6.00
Country Pub. USA
date 1216
------------------------------------------------------------
Author Jackway, P.T.;
Centre for Signal Processing Res., Queensland Univ. of Technol.,
Brisbane, Qld., Australia
Title Scale space properties of the multiscale morphological closing-
opening filter
Source ICIP 92. Proceedings of the 2nd Singapore International
Conference on Image Processing; Part: Singapore; Part: 7-11
Sept. 1992;
Singapore;
World Scientific;
xxii+734;
1992; pp. 278-81
Editor Srinivasa, V.; Ong Sim Heng; Ang Yew Hock
Abstract Scale-space is an important concept used in image and signal
processing and pattern recognition. Traditional scale-space is
generated by a linear Gaussian smoothing operation. The author
presents a nonlinear smoother corresponding to the multiscale
opening and closing operations of mathematical morphology which
also generates a scale-space. He shows that a parabolic
structuring element possesses desirable properties and
demonstrates the necessary monotonic scale-space property for
this structuring element
Thesaurus filtering and prediction theory; image processing; mathematical
morphology; pattern recognition; signal processing
Other Terms image processing; multiscale morphological closing-opening filter
; signal processing; pattern recognition; nonlinear smoother;
mathematical morphology; parabolic structuring element; scale-
space property
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4499038
AbstractNos. B9311-6140C-240; C9311-1250-171
ISBN or SBN 981 02 1182 1
References 11
Country Pub. Singapore
date 1205
------------------------------------------------------------
Author Kimia, B.B.; Tannenbaum, A.R.; Zucker, S.W.;
Brown Univ., Providence, RI, USA
Title Non-linear shape approximation via the entropy scale space
Source Geometric Methods in Computer Vision II; Part: San Diego, CA, USA
; Part: 12-13 July 1993;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.2031;
1993; pp. 218-33
Abstract A general theory of shape which unifies the two classical
approaches is organized around two basic intuitions: first, if a
boundary were changed only slightly, then in general its shape
would change only slightly. This leads to an operational theory
of shape based on incremental contour deformations. The second
intuition is that not all contours are shapes, but rather only
those that can enclose 'physical' material. A novel theory of
contour deformation is derived on the basis of abstract
conservation principles and Hamilton-Jacobi theory. The result is
a characterization of the computational elements of shape:
protrusions, parts, bends, and seeds (which show where to place
the components of a shape); and leads to a reaction-diffusion
space which places shapes within a neighborhood of 'similar' ones.
The entropy scale space is obtained from the reaction-diffusion
space by running the 'reaction' portion of the equations
'backwards' in time. As a result distinct components of a shape
can be removed by introducing a minimal disturbance to the
remainder of the shape. As such, the entropy scale space is a
combination of smoothing due to shocks as 'black holes' of
information and the subsequent rarefaction wave reconstruction
and the anisotropic diffusion process spreading of contour
information. This technique is numerically stable, and several
examples are shown
Thesaurus computer vision; convergence of numerical methods; entropy;
nonlinear differential equations; partial differential equations;
surface topography
Other Terms shape approximation; entropy scale space; operational theory of
shape; incremental contour deformations; Hamilton-Jacobi theory;
computational elements of shape; reaction-diffusion space;
rarefaction wave reconstruction; anisotropic diffusion process
ClassCodes B6140C; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4495186
AbstractNos. B9311-6140C-153; C9311-5260B-074
ISSN 0277786X
References 50
U.S. Copyright Clearance Center Code
0 8194 1280 5/93/$6.00
Country Pub. USA
date 1216
------------------------------------------------------------
Author Andersen, J.D.;
Dept. of Comput. Sci., Copenhagen Univ., Denmark
Title Methods for modeling the first layers of the retina
Source RNNS/IEEE Symposium on Neuroinformatics and Neurocomputers (Cat.
NO.92TH0483-8); Part: Rostov-on-Don, Russia; Part: 7-10 Oct.
1992;
Sponsored by: IEEE; Russian Neural Networks Soc;
new York, NY, USA;
IEEE;
2 vol. xxi+1270;
1992; pp. 179-86 vol.1
Abstract Recently, analog preprocessing circuits modeling the first layers
of the primate retina (low level vision) have been described. The
author compares the operation of these circuits with traditional
image preprocessing methods. Specifically, he investigates
properties and limitations of a machine vision based edge
detection method (inhomogeneous anisotropic diffusion) and makes
a comparison with silicon retina architectures. Anisotropic
diffusion is a modification of scale space filtering, disallowing
smoothing across pronounced image gradients (which are supposed
to reflect image edges). The silicon retina is an analog VLSI
realization mimicking the function of the first layers of the
primate retina. The silicon retina is shown to be faster and to
provide better segmentation results than diffusion methods
Thesaurus analogue processing circuits; biology computing; computer vision
; digital signal processing chips; edge detection; eye; image
segmentation; linear integrated circuits; vision; VLSI;
zoology
Other Terms analog preprocessing circuits; primate retina; low level vision;
image preprocessing methods; machine vision based edge
detection method; inhomogeneous anisotropic diffusion; scale
space filtering; image gradients; analog VLSI; segmentation;
Si retina architectures
ClassCodes A8732E; A4230V; B6140C; B1285; B2570; C5260B; C7330; C5160;
C5135
Article Type Practical; Experimental
Chemical Si/el
Language English
RecordType Conference
ControlNo. 4493808
AbstractNos. A9321-8732E-012; B9311-6140C-092; C9311-5260B-061
ISBN or SBN 0 7803 0809 3
References 15
Country Pub. USA
date 1206
------------------------------------------------------------
Author Jackway, P.T.;
Signal Process. Res. Centre, Queensland Univ. of Technol.,
Brisbane, Qld., Australia
Title Multiscale image processing: a review and some recent developments
Source Journal of Electrical and Electronics Engineering, Australia;
J. Electr. Electron. Eng. Aust. (Australia);
vol.13, no.2;
June 1993; pp. 88-98
Abstract Many fundamental operations in signal and image processing rely
on a smoothing or regularisation procedure. The degree of
smoothing or "scale" needs to be carefully selected for optimum
results. Instead of concentrating on image processing at a single
scale, "multiscale" techniques have recently been introduced to
take advantage of the information present at several different
scales in the signal. The concept of a "scale-space" provides a
way to relate the information obtained over different scales of
filter. The Gaussian filter is the only linear filter to possess
the required scale-space properties. However, the Gaussian filter
has some undesirable properties in two, and higher, dimensions
thus limiting the usefulness of Gaussian scale-space. The author
presents an overview of some recently developed nonlinear filters
which have good scale-space properties in higher dimensions.
These developments may open this field up to further study
Thesaurus filtering and prediction theory; image processing; mathematical
morphology; reviews
Other Terms multiscale image processing; review; smoothing; Gaussian filter
; nonlinear filters; scale-space properties; morphological
filter; regularisation procedure
ClassCodes B6140C; C1250
Article Type Bibliography/Literature Suvery; General or Review
Coden JEEADG
Language English
RecordType Journal
ControlNo. 4489122
AbstractNos. B9311-6140C-053; C9311-1250-032
ISSN 07252986
References 63
Country Pub. Australia
date 1215
------------------------------------------------------------
Author Deriche, R.; Giraudon, G.;
INRIA Sophia Antipolis, Valbonne, France
Title A computational approach for corner and vertex detection
Source International Journal of Computer Vision;
Int. J. Comput. Vis. (Netherlands);
vol.10, no.2;
April 1993; pp. 101-24
Abstract Corners and vertexes are strong and useful features in computer
vision for scene analysis, stereo matching, and motion analysis.
The authors deal with the development of a computational approach
to these important features. They consider first a corner model
and study analytically its behavior once it has been smoothed
using the well-known Gaussian filter. This allows them to clarify
the behavior of some well-known cornerness measure based
approaches used to detect these points of interest. Most of these
classical approaches appear to detect points that do not
correspond to the exact position of the corner. A new scale-space
based approach that combines useful properties from the Laplacian
and Beaudet's measure (1978) is then proposed in order to correct
and detect exactly the corner position. An extension of this
approach is then developed to solve the problem of trihedral
vertex characterisation and detection. In particular, it is shown
that a trihedral vertex has two elliptic maxima on extremal
contrast surfaces if the contrast is sufficient, and this allows
the authors to classify trihedral vertexes in two classes:
'vertex', and 'vertex as corner'. The corner-detection approach
developed is applied to accurately detect trihedral vertexes
using an additional test in order to make a distinction between
trihedral vertexes and corners. Many experiments have been
carried out using noisy synthetic data and real images containing
corners and vertexes. Most of the promising results obtained are
used to illustrate the experimental section
Thesaurus computational geometry; computer vision
Other Terms corner detection; computational approach; vertex detection;
computer vision; scene analysis; stereo matching; motion
analysis; Gaussian filter; scale-space based approach;
Beaudet's measure; trihedral vertex characterisation; elliptic
maxima; extremal contrast surfaces
ClassCodes C5260B; C1250; C4260
Article Type Practical
Coden IJCVEQ
Language English
RecordType Journal
ControlNo. 4476334
AbstractNos. C9310-5260B-088
ISSN 09205691
References 35
Country Pub. Netherlands
date 1213
------------------------------------------------------------
Author Whitten, G.;
Martin Marietta Lab., Balitmore, MD, USA
Title Scale space tracking and deformable sheet models for
computational vision
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.15, no.7;
July 1993; pp. 697-706
Abstract The deformable sheet, a physical model that provides a natural
framework for addressing many vision problems that can be solved
by smoothness-constrained optimization, is described. Deformable
sheets are characterized by a global energy functional, and the
smoothness constraint is represented by a linear internal energy
term. Analogous to physical sheets, the model sheets are deformed
by problem-specific external forces and, in turn, impose
smoothness on the applied forces. The model unifies the
properties of scale and smoothness into a single parameter that
makes it possible to perform scale space tracking by properly
controlling the smoothness constraint. Specifically, the desired
scale space trajectory is found by solving a differential
equation in scale. The simple analytic dependence on scale also
provides a mechanism for adaptive step size control. Results from
application of the deformable sheet model to various problems in
computational vision are presented
Thesaurus computer vision; image processing; optimisation
Other Terms deformable sheet models; computational vision; smoothness-
constrained optimization; global energy functional; smoothness
constraint; linear internal energy; scale space tracking;
differential equation
ClassCodes B6140C; B0260; C1250; C1180
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4465236
AbstractNos. B9310-6140C-015; C9310-1250-013
ISSN 01628828
References 21
U.S. Copyright Clearance Center Code
0162-8828/93/$03.00
Country Pub. USA
date 1216
------------------------------------------------------------
Author Gauch, J.M.; Pizer, S.M.;
Coll. of Comput. Sci., Northeastern Univ., Boston, MA, USA
Title Multiresolution analysis of ridges and valleys in grey-scale
images
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.15, no.6;
June 1993; pp. 635-46
Abstract Two methods for identifying and analyzing the multiresolution
behavior of ridges and valleys in grey-scale images are described.
The first method uses the tools of differential geometry to focus
on local image behavior. The resulting vertex curves mark the
tops of ridges and bottoms of valleys in an image. The second
method focuses on the global drainage patterns of rainfall on a
terrain map. The resulting watershed boundaries also identify the
tops of ridges and bottoms of valleys in an image. By following
these two geometric representations through scale space, the
authors build resolution hierarchies on ridges and valleys in the
image that can be utilized for interactive image segmentation
Thesaurus differential geometry; geophysical techniques; geophysics
computing; image segmentation; rain; remote sensing;
topography (Earth)
Other Terms remote sensing; geophysical techniques; ridges; valleys; grey-
scale images; multiresolution behavior; differential geometry;
vertex curves; global drainage patterns; rainfall; terrain map;
watershed boundaries; interactive image segmentation
ClassCodes A9385; A9365; A9110J; A9240E; B7710; B6140C; C7340; C5260B
Article Type Practical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4465230
AbstractNos. A9319-9385-009; B9310-7710-004; C9310-7340-013
ISSN 01628828
References 28
U.S. Copyright Clearance Center Code
0162-8828/93/$03.00
Country Pub. USA
date 1215
------------------------------------------------------------
Author Crespo, J.; Schafer, R.W.;
Sch. of Electr. Eng., Georgia Inst. of Tech., Atlanta, GA, USA
Title Image partition using an iterative multi-resolution smoothing
algorithm
Source ICASSP-92: 1992 IEEE International Conference on Acoustics,
Speech and Signal Processing (Cat. No.92CH3103-9); Part: San
Francisco, CA, USA; Part: 23-26 March 1992;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
5 vol. 3219;
1992; pp. 561-4 vol.3
Abstract An iterative algorithm for computing a family of piecewise-
constant approximations of images in scale space with variable
resolution is presented. The algorithm is a modification of an
iterative adaptive smoothing algorithm proposed by P. Saint-Marc
et al. (1991). The modification improves the behavior of the
algorithm when weak edges are present in the image. Edge
information computed from the image is incorporated into the
adaptive smoothing approach. The added iterative step does not
introduce a significant amount of computation, and the employment
of only local operators makes it well suited for a parallel
hardware implementation. The edges extracted must be two pixels
wide and exhibit high connectivity. A morphological edge operator
is presented to fulfil these requirements
Thesaurus edge detection; image segmentation; iterative methods;
mathematical morphology
Other Terms edge extraction; image partition; multi-resolution smoothing
algorithm; iterative algorithm; piecewise-constant
approximations; scale space; variable resolution; adaptive
smoothing; morphological edge operator
ClassCodes B6140C; B0290F; C1250; C4130
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4454548
AbstractNos. B9309-6140C-123; C9309-1250-110
ISBN or SBN 0 7803 0532 9
References 4
U.S. Copyright Clearance Center Code
0 7803 0532 9/92/$3.00
Country Pub. USA
date 1199
------------------------------------------------------------
Author Brockett, R.W.; Maragos, P.;
Div. of Appl. Sci., Harvard Univ., Cambridge, MA, USA
Title Evolution equations for continuous-scale morphology
Source ICASSP-92: 1992 IEEE International Conference on Acoustics,
Speech and Signal Processing (Cat. No.92CH3103-9); Part: San
Francisco, CA, USA; Part: 23-26 March 1992;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
5 vol. 3219;
1992; pp. 125-8 vol.3
Abstract Several nonlinear partial differential equations that model the
scale evolution associated with continuous-space multiscale
morphological erosions, dilations, openings, and closings are
discussed. These systems relate the infinitesimal evolution of
the multiscale signal ensemble in scale space to a nonlinear
operator acting on the space of signals. The type of this
nonlinear operator is determined by the shape and dimensionality
of the structuring element used by the morphological operators,
generally taking the form of nonlinear algebraic functions of
certain differential operators
Thesaurus image processing; mathematical morphology; nonlinear
differential equations
Other Terms evolution equations; continuous-scale morphology; nonlinear
partial differential equations; scale evolution; multiscale
morphological erosions; dilations; openings; closings;
multiscale signal ensemble; scale space; nonlinear operator;
structuring element; morphological operators; nonlinear
algebraic functions; differential operators
ClassCodes B6140C; B0220
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4445906
AbstractNos. B9308-6140C-203
ISBN or SBN 0 7803 0532 9
References 11
U.S. Copyright Clearance Center Code
0 7803 0532 9/92/$3.00
Country Pub. USA
date 1199
------------------------------------------------------------
Author Acton, S.T.; Bovik, A.C.;
Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
Title Anisotropic edge detection using mean field annealing
Source ICASSP-92: 1992 IEEE International Conference on Acoustics,
Speech and Signal Processing (Cat. No.92CH3103-9); Part: San
Francisco, CA, USA; Part: 23-26 March 1992;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
5 vol. 3219;
1992; pp. 393-6 vol.2
Abstract An edge detection technique that optimizes edge localization
while providing edge continuity and edge thinning is introduced.
The solution is obtained by annealing a mean field neural network,
providing inexpensive solutions with high parameter insensitivity.
Anisotropic diffusion is used to provide localized edge data
through the scale-space. Analysis of network parameters,
diffusion parameters, network convergence, and scale-space
equivalence is provided. Results are shown for real image data
and compared with the results of other important edge detection
schemes
Thesaurus edge detection; neural nets
Other Terms anisotropic edge detection; anisotropic diffusion; mean field
annealing; edge localization; edge continuity; edge thinning;
mean field neural network; parameter insensitivity; localized
edge data; scale-space; network parameters; diffusion
parameters; network convergence; real image data
ClassCodes B6140C; C1250; C1230D
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4441475
AbstractNos. B9308-6140C-145; C9308-1250-120
ISBN or SBN 0 7803 0532 9
References 6
U.S. Copyright Clearance Center Code
0 7803 0532 9/92/$3.00
Country Pub. USA
date 1199
------------------------------------------------------------
Author Wong, Y.; Posner, E.C.;
Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA,
USA
Title Scale-space clustering and classification of SAR images with
numerous attributes and classes
Source Proceedings. IEEE Workshop on Applications of Computer Vision
(Cat. No.92TH0446-5); Part: Palm Springs, CA, USA; Part: 30 Nov.
-2 Dec. 1992;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xi+317;
1992; pp. 74-81
Abstract Describes application of scale-space clustering to the
classification of a multispectral and polarimetric SAR image of
an agricultural site. After polarimetric and radiometric
calibration and noise cancellation, the authors extracted a 12-
dimensional feature vector for each pixel from the scattering
matrix. The algorithm was able to partition without supervision a
set of unlabeled vectors from 13 selected sites, each site
corresponding to a distinct crop, into 13 clusters. The cluster
parameters were then used to classify the whole image. The
classification map is much less noisy and more accurate than
those obtained by hierarchical rules. The algorithm can handle
variabilities in cluster densities, cluster sizes and ellipsoidal
shapes
Thesaurus agriculture; image recognition; remote sensing by radar;
synthetic aperture radar
Other Terms scale-space clustering; SAR image; agricultural site;
classification map; variabilities; cluster densities
ClassCodes B7730; B6300; C5260B
Article Type Practical
Language English
RecordType Conference
ControlNo. 4437615
AbstractNos. B9308-7730-003; C9308-5260B-062
ISBN or SBN 0 8186 2840 5
References 20
U.S. Copyright Clearance Center Code
0 8186 2840 5/92/$03.00
Country Pub. USA
date 1207
------------------------------------------------------------
Author Rangarajan, K.; Allen, W.; Shah, M.;
Dept. of Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
Title Matching motion trajectories using scale-space
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.26, no.4;
April 1993; pp. 595-610
Abstract The goal is to design a recognition system which can distinguish
between two objects with the same shape but different motion, or
between two objects with the same motion but a different shape.
The input to the system is a set of two-dimensional (2D)
trajectories from an object tracked through a sequence of n
frames. The structure and three-dimensional (3D) trajectories of
each object in the domain are stored in the model. The problem is
to match the information in the model with the input set of 2D
trajectories and determine if they represent the same object. The
simplest way to perform these steps is to match the input 2D
trajectories with the 2D projections of the 3D model trajectories.
First, a simple algorithm is presented which matches two single
trajectories using only motion information. The 2D motion
trajectories are converted into two one-dimensional (1D) signals
based on their speed and direction components. The signals are
then represented by scale-space images, both to simplify matching
and because the scale-space representations are translation and
rotation invariant. The matching algorithm is extended to include
spatial information and a second algorithm is proposed which
matches multiple trajectories by combining motion and spatial
match scores. Both algorithms are tested with real and synthetic
data
Thesaurus image recognition; motion estimation
Other Terms 2D trajectories; translation invariant; 3D trajectories; speed
components; motion trajectories; scale-space; recognition
system; shape; input set; model trajectories; direction
components; rotation invariant; spatial information
ClassCodes C5260B; C1250
Article Type Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 4436481
AbstractNos. C9308-5260B-036
ISSN 00313203
References 8
U.S. Copyright Clearance Center Code
0031-3203/93/$6.00+.00
Country Pub. UK
date 1213
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Author Mori, K.; Doi, S.; Matsuda, M.;
Osaka Electro-Commun. Univ., Japan
Title The approach of the real-time underwater data transmission system
based on scale-space filtering
Source Transputer/Occam. Japan 4. Proceedings of the 4th
Transputer/Occam International Conference; Part: Tokyo, Japan; Pa
rt: 4-5 June 1992;
Sponsored by: Inmos; Nikkan Kogyo Shimbun;
Amsterdam, Netherlands;
IOS Press;
ix+268;
1992; pp. 121-36
Editor Noguchi, S.; Umeo, H.
Abstract Underwater data transmission using scale-space filtering and
fingerprint pattern keying as the data transmission method is
proposed. The design of the real-time underwater data
transmission system is presented. The matching method using the
number of the zero-cross points in fingerprint pattern keying is
also discussed as one of the data transmission methods which is
conscious of real-time processing. From two types of simulations
on a transputer array, where one is the division by the scale
parameter sigma /sub j/ and the other is pipeline-processing
using only one scale parameter, the possibility about the real-
time processing of this system is discussed using experimental
results which are the execution time on a transputer array
Thesaurus acoustic signal processing; codes; data communication systems;
filtering and prediction theory; parallel algorithms; real-time
systems; transputer systems
Other Terms real-time underwater data transmission system; scale-space
filtering; fingerprint pattern keying; matching method; zero-
cross points; transputer array; scale parameter; pipeline-
processing
ClassCodes B6140; B6120B; B6210; C5620; C5260; C1260; C6130
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4412649
AbstractNos. B9307-6140-046; C9307-5620-049
References 7
Country Pub. Netherlands
date 1202
------------------------------------------------------------
Author Blom, J.; Ter Haar Romeny, B.M.; Bel, A.; Koenderink, J.J.;
Buys Ballot Lab., Utrecht Univ., Netherlands
Title Spatial derivatives and the propagation of noise in Gaussian
scale space
Source Journal of Visual Communication and Image Representation;
J. Vis. Commun. Image Represent. (USA);
vol.4, no.1;
March 1993; pp. 1-13
Abstract Image structure analysis requires the computation of local
spatial derivatives of the intensity distribution. These are
determined by convolution with Gaussian derivative operators.
Noise is enhanced by the high-pass nature of differentiation,
particularly at high order. On the other hand, the Gaussian-
weighted averaging gives rise to noise reduction. The author
gives an analysis of the propagation of spatially uncorrelated as
well as spatially correlated additive noise in scale space, when
the noise is subjected to fuzzy derivative operators of any order.
The propagation of noise variance is always substantially reduced
when scale is increased, the effect being greater for higher
order derivatives. The spatial blurring is always predominant, or,
the representation of the noise and its derivatives is
substantial only at the original (inner) scale. Expressions are
derived for the propagation of noise in functions of derivatives,
like the Laplacian and isophote curvature. All expressions are
evaluated for a D-dimensional (image) data structure. Determining
derivatives, even up to high order, combined with scale space, is
a very robust and stable operation. The important conclusion is
that the use of differential geometrical methods in scale space,
particularly in noisy images, is justified
Thesaurus correlation theory; edge detection; filtering and prediction
theory; image processing; noise; spatial filters
Other Terms noise propagation; image structure analysis; Laplacian operator;
edge detection; filtering; Gaussian scale space; local
spatial derivatives; intensity distribution; spatially
correlated additive noise; fuzzy derivative operators; spatial
blurring; isophote curvature
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden JVCRE7
Language English
RecordType Journal
ControlNo. 4406258
AbstractNos. B9306-6140C-231; C9306-1250-189
ISSN 10473203
References 22
U.S. Copyright Clearance Center Code
1047-3203/93/$5.00
Country Pub. USA
date 1212
------------------------------------------------------------
Author Kube, P.;
Dept. of Comput. Sci. & Eng., California Univ., San Diego, La
Jolla, CA, USA
Title Properties of energy edge detectors
Source Proceedings. 1992 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.92CH3168-2); Part:
Champaign, IL, USA; Part: 15-18 June 1992;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xvi+870;
1992; pp. 586-91
Abstract The author introduces a framework for investigating the
properties of energy edge detectors and uses it to derive some
results of interest. He shows a necessary condition on the form
of constituent linear filters in quadratic detectors, subject to
some conditions, and demonstrates some limitations of such
detectors. It is shown that no quadratic detector can detect an
edge at 0 for both a sinewave and a cosine wave, which has
implications for detecting narrowband edges with spatially local
filters. It is also shown that the scale-space behavior of energy
detectors is not well-behaved, in that it contains bifurcations
as scale increases, i.e. new edges can be created as the image is
smoothed
Thesaurus image segmentation; pattern recognition
Other Terms energy edge detectors properties; necessary condition;
constituent linear filters; quadratic detectors; sinewave;
cosine wave; spatially local filters; scale-space behavior;
bifurcations
ClassCodes B6140C; C1250; C5260B
Article Type Practical
Language English
RecordType Conference
ControlNo. 4399892
AbstractNos. B9306-6140C-189; C9306-1250-150
ISBN or SBN 0 8186 2855 3
References 12
U.S. Copyright Clearance Center Code
0 8186 2855 3/92$03.00
Country Pub. USA
date 1202
------------------------------------------------------------
Author Whitaker, R.T.; Pizer, S.M.;
Dept. of Comput. Sci., North Carolina Univ., Chapel Hill, NC, USA
Title A multi-scale approach to nonuniform diffusion
Source CVGIP: Image Understanding;
CVGIP, Image Underst. (USA);
vol.57, no.1;
Jan. 1993; pp. 99-110
Abstract The paper examines a new method of image processing that combines
information at multiple scales in order to locate boundaries. The
method employs a technique of edge-affected diffusion, where
blurring is limited by the presence of edges as measured at the
scale of interest. By repeating such processing and measuring
gradients at successively smaller one is able to trace a 'path'
through scale space which can preserve accurate information about
boundaries of objects, and yet selectively remove objects that
fall below a scale of interest. The authors compared this
approach with the anisotropic diffusion technique described by
Perona and Malik (IEEE Trans. Pattern Anal. Mach. Intell. vol.12,
p.429-39, 1990), which depends only on the local gradient of
intensity of the processed image. The authors show some examples
which indicate that this method could be useful for boundary
detection in the presence of blurring and noise and which is also
capable of performing grouping of distinct objects at various
scales. The paper also examines the sensitivity of this process
with respect to one's choice of parameters
Thesaurus edge detection
Other Terms image processing; edge-affected diffusion; blurring; boundary
detection
ClassCodes B6140C; C5260B; C1250; C1260
Article Type Theoretical / Mathematical; Experimental
Coden CIUNEJ
Language English
RecordType Journal
ControlNo. 4398172
AbstractNos. B9306-6140C-150; C9306-5260B-122
ISSN 10499660
References 13
U.S. Copyright Clearance Center Code
1049-9660/93/$5.00
Country Pub. USA
date 1210
------------------------------------------------------------
Author Raman, S.V.; Sarkar, S.; Boyer, K.L.;
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Title Hypothesizing structures in edge-focused cerebral magnetic
resonance images using graph-theoretic cycle enumeration
Source CVGIP: Image Understanding;
CVGIP, Image Underst. (USA);
vol.57, no.1;
Jan. 1993; pp. 81-98
Abstract The authors present a novel method for the automatic generation
of structure hypotheses (that is, educated guesses) suitable for
recognition in medical images. They base their approach on
segment-based edge-focusing to delineate significant boundaries
precisely, and graph-theoretic cycle enumeration to produce
natural closures and, therefore, plausible tissue structures of
interest from incomplete boundary information. An efficient edge
focusing algorithm selects significant fine scale boundaries as
those natural descendants (in scale space) of prominent coarse
scale edges. The fine scale representation provides the
localization precision necessary, while the focusing ensures that
only significant contours surviving over a range of scales are
considered and so eliminates much of the 'clutter' associated
with a fine scale edge map. The spatial relationships among the
edge segments are stored in the form of a directed graph.
Possible extensions (closures) of broken edge segments are
searched using time- and space-efficient voting methods. Cycle
enumeration techniques for directed graphs then generate the
structure hypotheses
Thesaurus biomedical NMR; brain; directed graphs; edge detection;
feature extraction; image recognition
Other Terms hypothesis generation; edge-focused cerebral magnetic resonance
images; graph-theoretic cycle enumeration; medical images;
segment-based edge-focusing; tissue structures; incomplete
boundary information; edge focusing algorithm; fine scale
boundaries; coarse scale edges; fine scale representation;
localization precision; significant contours; spatial
relationships; edge segments; directed graph; broken edge
segments; voting methods; structure hypotheses
ClassCodes A8770E; A8740; A8760G; B6140C; B7510B; C7330; C5260B; C1160
Article Type Practical; Theoretical / Mathematical; Experimental
Coden CIUNEJ
Language English
RecordType Journal
ControlNo. 4398171
AbstractNos. A9311-8770E-015; B9306-6140C-149; C9306-7330-049
ISSN 10499660
References 36
U.S. Copyright Clearance Center Code
1049-9660/93/$5.00
Country Pub. USA
date 1210
------------------------------------------------------------
Author Xu Zhi Xiang; Wang Jijie;
Shangai Univ. of Sci. & Technol., China
Title Performances of the Laplacian of binomial distribution and the
discrete Laplacian of Gaussian edge detection operators
Source Acta Electronica Sinica;
Acta Electron. Sin. (China);
vol.20, no.11;
Nov. 1992; pp. 69-74
Abstract Presents a performance analysis and comparison between the
Laplacian of binomial distribution (LOB) and the discrete
Laplacian of Gaussian (DLOG) edge detection operators in the
space domain and frequency domain. When the scale space constants
of the two edge detection operators are large enough, the
characteristics in space domain and frequency domain and
performances in image edge detection are almost the same. But
when the scale space constants are smaller, the conclusion can be
made that the performances of LOB operator are little better than
that of discrete LOG operator after comparisons of central
frequency, 3dB bandwidth and high frequency attenuation rate at
cut off frequency in frequency domain. LOB operator may be
considered as a discrete realization of LOG operator. The
experiments are given to verify the correctness of analysis
Thesaurus edge detection
Other Terms Laplacian; binomial distribution; discrete Laplacian; Gaussian
edge detection operators; performance analysis; space domain;
frequency domain; scale space constants; image edge detection;
LOB operator; discrete LOG operator; central frequency; 3dB
bandwidth; frequency attenuation rate; cut off frequency;
correctness
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden TTHPAG
Language Chinese
RecordType Journal
ControlNo. 4396136
AbstractNos. B9306-6140C-137; C9306-1250-106
ISSN 03722112
References 3
Country Pub. China
date 1207
------------------------------------------------------------
Author Wong, Y.-F.;
Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA,
USA
Title Clustering data by melting
Source Neural Computation;
Neural Comput. (USA);
vol.5, no.1;
Jan. 1993; pp. 89-104
Abstract The author derives a new clustering algorithm based on
information theory and statistical mechanics, which is the only
algorithm that incorporates scale. It also introduces a new
concept into clustering: cluster independence. The cluster
centers correspond to the local minima of a thermodynamic free
energy, which are identified as the fixed points of a one-
parameter nonlinear map. The algorithm works by melting the
system to produce a tree of clusters in the scale space. Melting
is also insensitive to variability in cluster densities, cluster
sizes, and ellipsoidal shapes and orientations. The authors
tested the algorithm successfully on both simulated data and a
synthetic aperture radar image of an agricultural site with 12
attributes for crop identification
Thesaurus information theory; pattern recognition; remote sensing by radar
; statistical mechanics
Other Terms clustering algorithm; information theory; statistical mechanics;
cluster independence; cluster centers; local minima;
thermodynamic free energy; one-parameter nonlinear map; melting;
scale space; cluster densities; cluster sizes; ellipsoidal
shapes; orientations; synthetic aperture radar image;
agricultural site; crop identification
ClassCodes C1260; C1250; C1180
Article Type Theoretical / Mathematical
Coden NEUCEB
Language English
RecordType Journal
ControlNo. 4393900
AbstractNos. C9306-1260-022
ISSN 08997667
References 24
Country Pub. USA
date 1210
------------------------------------------------------------
Author Eggert, D.W.; Bowyer, K.W.; Dyer, C.R.; Christensen, H.I.;
Goldgof, D.B.;
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL,
USA
Title The scale space aspect graph
Source Proceedings. 1992 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.92CH3168-2); Part:
Champaign, IL, USA; Part: 15-18 June 1992;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xvi+870;
1992; pp. 335-40
Abstract Currently the aspect graph is computed under the assumption of
perfect resolution in the viewpoint, the projected image, and the
object shape. Visual detail is represented that an observer might
never see in practice. By introducing scale into this framework,
a mechanism is provided for selecting levels of detail that are
large enough to merit explicit representation, effectively
allowing control over the size of the aspect graph. To this end
the scale space aspect graph is introduced, and an interpretation
of the scale dimension in terms of the spatial extent of image
features is considered. A brief example is given for polygons in
a plane
Thesaurus graphs; image recognition
Other Terms detail representation; scale space aspect graph; perfect
resolution; projected image; object shape; levels of detail;
image features; polygons
ClassCodes C5260B; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4382947
AbstractNos. C9305-5260B-085
ISBN or SBN 0 8186 2855 3
References 22
U.S. Copyright Clearance Center Code
0 8186 2855 3/92$03.00
Country Pub. USA
date 1202
------------------------------------------------------------
Author Fermuller, C.; Kropatsch, W.;
Comput. Vision Lab., Maryland Univ., College Park, MD, USA
Title Multi-resolution shape description by corners
Source Proceedings. 1992 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.92CH3168-2); Part:
Champaign, IL, USA; Part: 15-18 June 1992;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xvi+870;
1992; pp. 271-6
Abstract A robust method for describing planar curves in multiple
resolution using curvature information is presented. The method
is developed by taking into account the discrete nature of
digital images as well as the discrete aspect of a
multiresolution structure (pyramid). The main contribution lies
in the robustness of the technique, which is due to the
additional information that is extracted from observing the
behavior of corners in the whole pyramid. Furthermore, the
resulting algorithm is conceptually simple and easily
parallelizable. Theoretical results are developed analyzing the
curvature of continuous curves in scale-space and showing the
behavior of curvature extrema under varying scale. The results
are used to eliminate any ambiguities that might arise from
sampling problems due to the discreteness of the representation.
Experimental results demonstrate the potential of the method
Thesaurus computational geometry; computer vision; curve fitting;
feature extraction; image processing
Other Terms planar curves; multiple resolution; curvature information;
digital images; multiresolution structure; robustness; corners;
parallelizable; continuous curves; scale-space; curvature
extrema; varying scale; ambiguities
ClassCodes C5260B; C4260
Article Type Experimental
Language English
RecordType Conference
ControlNo. 4382937
AbstractNos. C9305-5260B-075
ISBN or SBN 0 8186 2855 3
References 16
U.S. Copyright Clearance Center Code
0 8186 2855 3/92$03.00
Country Pub. USA
date 1202
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------------------------------------------------------------
Author Mjolsness, E.;
Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA
Title Visual grammars and their neural networks
Source Science of Artificial Neural Networks; Part: Orlando, FL, USA; Pa
rt: 21-24 April 1992;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1710, pt.1;
1992; pp. 63-85 vol.1
Abstract Exhibits a systematic way to derive neural nets for vision
problems. It involves formulating a vision problem as Bayesian
inference or decision on a comprehensive model of the visual
domain given by the probabilistic grammar. A key feature of this
grammar is the way in which it eliminates model information, such
as object labels, as it produces an image; correspondance
problems and other noise removal tasks result. The neural nets
that arise most directly are generalized assignment networks.
Also there are transformations which naturally yield improved
algorithms such as correlation matching in scale space and the
Frameville neural nets for high-level vision. Networks derived
this way generally have objective functions with spurious local
minima; such minima may commonly be avoided by dynamics that
include deterministic annealing, for example recent improvements
to Mean Field Theory dynamics. The grammatical method of neural
net design allows domain knowledge to enter from all levels of
the grammar, including 'abstract' levels remote from the final
image data, and may permit new kinds of learning as well
Thesaurus computer vision; grammars; inference mechanisms; neural nets
Other Terms neural nets; vision problems; Bayesian inference;
probabilistic grammar; domain knowledge
ClassCodes C1230D; C1250; C4210; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4374026
AbstractNos. C9305-1230D-044
ISSN 0277786X
References 27
U.S. Copyright Clearance Center Code
0 8194 0875 1/92/$4.00
Country Pub. USA
date 1200
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Author Trucco, E.;
Dept. of Artificial Intelligence, Edinburgh Univ., UK
Title On shape-preserving boundary conditions for diffusion smoothing
Source Proceedings. 1992 IEEE International Conference on Robotics And
Automation (Cat. No.92CH3140-1); Part: Nice, France; Part: 12-
14 May 1992;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
3 vol. xxxix+2819;
1992; pp. 1690-4 vol.2
Abstract Several boundary treatments for attenuating shape deformation
introduced by Gaussian smoothing are discussed. The author models
Gaussian smoothing by a diffusion equation, a general
mathematical framework particularly useful for scale-space
analysis. An adaptive, shape-reserving boundary condition for
diffusion smoothing range images is introduced. It is shown that
this condition is more general than similar techniques found in
the literature
Thesaurus adaptive systems; filtering and prediction theory; image
processing; sensor fusion
Other Terms image analysis; shape-preserving boundary conditions; diffusion
smoothing; shape deformation; Gaussian smoothing; scale-space
analysis; range images
ClassCodes B6140C; C1250; C1260; C1240
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4368196
AbstractNos. B9304-6140C-182; C9304-1250-137
ISBN or SBN 0 8186 2720 4
References 15
U.S. Copyright Clearance Center Code
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Country Pub. USA
date 1201
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Author Woo Young Choi; Rae-Hong Park;
Dept. of Electr. Eng., Myongji Univ., Seoul, South Korea
Title Stereo matching using dynamic programming in scale-space
Source Journal of the Korean Institute of Telematics and Electronics;
J. Korean Inst. Telemat. Electron. (South Korea);
vol.29B, no.8;
Aug. 1992; pp. 44-53
Abstract In this paper, a matching method is proposed to improve the
correct matching rate in stereo correspondence matching in which
the fingerprint of zero-crossing points on the scale-space is
used as the robust matching feature. Dynamic programming, which
is appropriate for the fingerprint feature, is introduced for
correspondence matching. The authors also improve the matching
rate by using the post-processing for correcting mismatched
points. In simulation, they apply the proposed algorithm to the
synthetic and real images and obtain good matching results
Thesaurus dynamic programming; feature extraction; image recognition
Other Terms synthetic images; dynamic programming; scale-space; matching
rate; correspondence matching; fingerprint; zero-crossing
points; robust matching feature; post-processing; real images
ClassCodes B6140C; B0260; C1250; C1180
Article Type Theoretical / Mathematical
Coden CKNOEZ
Language Korean
RecordType Journal
ControlNo. 4365921
AbstractNos. B9304-6140C-154; C9304-1250-118
ISSN 1016135X
References 12
Country Pub. South Korea
date 1204
------------------------------------------------------------
Author Soo-Chang Pei; Chao-Nan Lin;
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Title The detection of dominant points on digital curves by scale-space
filtering
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.25, no.11;
Nov. 1992; pp. 1307-14
Abstract An effective method of scale-space filtering with a Gaussian
kernel is introduced to detect dominant points on digital curves.
The conventional polygonal approximation algorithms are time-
consuming and need input parameter tuning for Gaussian smoothing
the noise and quantization error, also they are sensitive to
scaling and rotation of the object curve. The above difficulty
can be overcome by finding out the dominant points at each scale
by scale-space filtering. By tracing back the dominant point
contours in the scale-space image, the stable cardinal curvature
points can be detected very accurately. This new method requires
no input parameters, and the resultant dominant points do not
change under translation, rotation and scaling. A fast
convolution algorithm is proposed to detect the dominant points
at each scale
Thesaurus filtering and prediction theory; image recognition
Other Terms dominant point detection; Gaussian smoothing; image recognition;
digital curves; scale-space filtering; scale-space image;
stable cardinal curvature points; fast convolution algorithm
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 4361821
AbstractNos. B9304-6140C-124; C9304-1250-095
ISSN 00313203
References 19
U.S. Copyright Clearance Center Code
0031-3203/92/$5.00+.00
Country Pub. UK
date 1207
------------------------------------------------------------
Author de Ridder, H.;
Inst. for Perception Res., Eindhoven, Netherlands
Title Minkowski-metrics as a combination rule for digital-image-coding
impairments
Source Human Vision, Visual Processing and Digital Display III; Part:
San Jose, CA, USA; Part: 10-13 Feb. 1992;
Sponsored by: SPIE; Soc. Imaging Sci. Technol;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1666;
1992; pp. 16-26
Abstract The urge to compress the amount of information needed to
represent digitized images while preserving perceptual image
quality has led to a plethora of image-coding algorithms. At high
data compression ratios, these algorithms usually introduce
several coding artifacts. For the evaluation of image-coding
algorithms, it is important to find out how these impairments
combine and how this can be described. The objective is to show
that Minkowski-metrics can be used as a combination rule for
small impairments like those usually encountered in digitally
coded images. An experiment has been conducted in which subjects
assessed the perceptual quality of scale-space-coded color images
comprising three kinds of impairment, namely 'unsharpness',
'phantoms' (dark/bright patches within bright/dark homogeneous
regions) and 'color desaturation'. The results show an
accumulation of these impairments that is efficiently described
by a Minkowski-metric with an exponent of about two
Thesaurus colour vision; image coding; visual perception
Other Terms digital-image-coding impairments; perceptual image quality;
plethora; data compression; Minkowski-metrics; scale-space-
coded color images; unsharpness; phantoms; color desaturation
ClassCodes A4230V; A8732S; A8732N; B6140C; B6120B; C1250; C5260B
Article Type Experimental
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4337828
AbstractNos. A9306-4230-002; B9303-6140C-137; C9303-1250-126
ISSN 0277786X
References 19
U.S. Copyright Clearance Center Code
0 8194 0820 4/92/$4.00
Country Pub. USA
date 1198
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Author Vandenberg, S.; Osborne, C.F.;
Dept. of Phys., Monash Univ., Caulfield East, Vic., Australia
Title Digital image processing techniques, fractal dimensionality and
scale-space applied to surface roughness
Source Wear;
Wear (Switzerland);
vol.159, no.1;
2 Nov. 1992; pp. 17-30
Abstract Surface roughness is a result of the existence of peaks and
troughs in the surface. Measurement of the surface topography is
controlled by the resolution of the probe (e.g. a diamond stylus,
a laser beam) and the literature shows that the predicted
topography has great sensitivity to the probe dimensions. Image
analysis techniques are applied to the topography of the surface
and the properties of the surface are predicted on the assumption
that the surface is modellable by two-dimensional random noise. A
fractal model is applied to the model of the noise and the
limitations of this model are investigated with respect to
sampling and digitization. Finally the ideas of 'scale-space' are
applied to the images to establish the nature of the basic
roughness elements which describe the surfaces under consideration
Thesaurus fractals; physics computing; surface topography
Other Terms digital image processing technique; fractal dimensionality;
surface roughness; surface topography; two-dimensional random
noise
ClassCodes A6820; C7320
Article Type Theoretical / Mathematical
Coden WEARCJ
Language English
RecordType Journal
ControlNo. 4335470
AbstractNos. A9305-6820-022; C9303-7320-089
ISSN 00431648
References 33
U.S. Copyright Clearance Center Code
0043-1648/92/$5.00
Country Pub. Switzerland
date 1207
------------------------------------------------------------
Author Chung-Lin Huang; Tai-Yuen Cheng; Chaur-Chin Chen;
Dept. of Electr. Eng., Nat. Tsing-Hua Univ., Hsin-Chu, Taiwan
Title Color images' segmentation using scale space filter and Markov
random field
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.25, no.10;
Oct. 1992; pp. 1217-29
Abstract A hybrid method is presented that combines the scale space filter
(SSF) and Markov random field (MRF) for color image segmentation.
The fundamental idea of the SSF is to use the convolution of
Gaussian functions and an image-histogram to generate a scale
space image and then find the proper interval bounded by the
local extrema of the derivatives. The Gaussian function is with
zero mean and varied standard deviation. Using the SSF the
different scaled histogram is separated into intervals
corresponding to peaks and valleys. The MRF makes use of the
property that each pixel in an image has some relationship with
other pixels. The basic construction of an MRF is a joint
probability given the original data. The original data is the
image that is obtained from the source and the result is called
the label image. Because the MRF needs a number of segments
before it converges to the global minimum, the SSF is exploited
to do coarse segmentation and then MRF is used to do fine
segmentation of the images. Basically, the former is histogram-
based segmentation, whereas the latter is neighborhood-based
segmentation
Thesaurus image segmentation; Markov processes; simulated annealing;
spatial filters
Other Terms spatial filters; simulated annealing; Gibbs sampling; scale
space filter; Markov random field; color image segmentation;
convolution; Gaussian functions; image-histogram; coarse
segmentation; fine segmentation; neighborhood-based segmentation
ClassCodes B6140C; B0240Z; B0260; C1250; C1140Z; C1180
Article Type Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 4329058
AbstractNos. B9303-6140C-043; C9303-1250-037
ISSN 00313203
References 18
U.S. Copyright Clearance Center Code
0031-3203/92/$5.00+.00
Country Pub. UK
date 1206
------------------------------------------------------------
Author Goshtasby, A.;
Dept. of Electr. Eng. & Comput. Sci., Coll. of Eng., Chicago, IL,
USA
Title Parametric representation of digital shapes by Gaussian functions
Source Computer Aided Design;
Comput. Aided Des. (UK);
vol.24, no.12;
Dec. 1992; pp. 659-65
Abstract A new formulation for parametric curves is given. In the proposed
formulation, each component of a curve is defined independently
of the other components and with different knots. A curve is
represented by a blending of Gaussian functions. The Gaussian
functions are estimated by the scale-space analysis of a digital
shape. The estimated Gaussian functions are then refined by the
Marquardt algorithm to minimize the root-mean-squared error
between the curve and the shape. Numerical examples are given
showing the accuracy and compression rate of the proposed
parametric curve in the representation of digital shapes
Thesaurus computational geometry; curve fitting; data compression; image
processing
Other Terms parametric representation; digital shapes; Gaussian functions;
parametric curves; scale-space analysis; digital shape;
Marquardt algorithm; root-mean-squared error; compression rate
ClassCodes C4260; C4130; C5260B
Article Type Practical; Theoretical / Mathematical
Coden CAIDA5
Language English
RecordType Journal
ControlNo. 4326506
AbstractNos. C9303-4260-003
ISSN 00104485
References 30
U.S. Copyright Clearance Center Code
0010-4485/92/120659-07$3.00
Country Pub. UK
date 1208
------------------------------------------------------------
Author Nguyen, T.C.; Huang, T.S.;
Beckman Inst. & Coordinated Sci. Lab., Urbana, IL, USA
Title Image blurring effects due to depth discontinuities: blurring
that creates emergent image details
Source Image and Vision Computing;
Image Vis. Comput. (UK);
vol.10, no.10;
Dec. 1992; pp. 689-98
Abstract A new model (called multi-component blurring-or MCB) to account
for image blurring effects due to depth discontinuities is
presented. It is shown that blurring processes operating in the
vicinity of large depth discontinuities can give rise to emergent
image details. In other words, the maximum principle for scale
space does not hold. It is argued that blurring in high-relief 3D
scenes should be more accurately modelled as a multi-component
process. Results are presented from extensive and carefully
designed experiments, with many images of real scenes taken by a
CCD camera with typical parameters. These results have
consistently supported the new blurring model. Due care was taken
to ensure that the image phenomena observed are mainly due to
defocussing and not due to mutual illuminations, specularity,
objects' 'finer' structures, coherent diffraction, or incidental
image noises. The paper also hypothesizes on the role of blurring
on human depth-from-blur perception, based on correlation with
recent results from human blur perception
Thesaurus computer vision; image recognition
Other Terms depth discontinuities; emergent image details; multi-component
blurring; image blurring; high-relief 3D scenes; real scenes;
CCD camera; defocussing; human depth-from-blur perception
ClassCodes B6140C; C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Coden IVCODK
Language English
RecordType Journal
ControlNo. 4320317
AbstractNos. B9302-6140C-221; C9302-1250-195
ISSN 02628856
References 20
U.S. Copyright Clearance Center Code
0262-8856/92/010689-10$3.00
Country Pub. UK
date 1208
------------------------------------------------------------
Author Jang, B.K.; Chin, R.T.;
Health Sci. Res. Lab., Eastman Kodak Co., Rochester, NY, USA
Title Gaussian and morphological scale space for shape analysis
Source Asia-Pacific Engineering Journal, Part A (Electrical Engineering);
Asia-Pac. Eng. J. A, Electr. Eng. (Singapore);
vol.2, no.2;
June 1992; pp. 165-202
Abstract Multiscale image representations, or scale space, have been
utilized in coarse-to-fine image processing, in which the image
is represented by sets of features, each set presented at a
different scale. A one-dimensional signal can be represented as a
two-dimensional scale space in which feature locations are
encoded spatially and their evolution through scale is encoded in
the second dimension resulting in two-dimensional line patterns.
A two-dimensional image in turn produces a three-dimensional
scale space of surfaces. The idea behind scale space is based on
the fact that single-scale representations and single-scale
processing are inadequate in many applications because an image
cannot categorically be assumed to have only features of a single
size. Scale space has been successfully applied to applications
such as noise filtering, corner detection, and recognition. The
construction of scale space requires the smoothing of the given
image to generate a set of corresponding images at other coarser
scales, and the extraction of features at these scales. Various
methods of smoothing combined with various feature extractors
will result in drastically different scale space representations.
The particular application and desired criteria determine the
choice of smoothing and feature extractor. This paper reviews the
Gaussian and morphological scale space for planar shape analysis.
The discussion of the various scale space methods is organized
into three categories-boundary approach, region approach and
hybrid approach. Properties, limitations, performance and
applications of these scale space methods are discussed. A number
of examples are given to illustrate the various essential
properties and problems associated with scale space
Thesaurus feature extraction; filtering and prediction theory; image
recognition
Other Terms morphological scale space; shape analysis; coarse-to-fine image
processing; one-dimensional signal; two-dimensional scale space;
feature locations; two-dimensional line patterns; three-
dimensional scale space; noise filtering; corner detection;
smoothing; boundary approach; region approach; hybrid approach
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden APEJEM
Language English
RecordType Journal
ControlNo. 4317702
AbstractNos. B9302-6140C-204; C9302-1250-184
ISSN 01295411
References 277
Country Pub. Singapore
date 1202
------------------------------------------------------------
Author Morita, S.; Kawashima, T.; Aoki, Y.;
Fac. of Eng., Hokkaido Univ., Sapporo, Japan
Title Generation of hierarchical description for smooth curved surfaces
Source Transactions of the Institute of Electronics, Information and
Communication Engineers D-II;
Trans. Inst. Electron. Inf. Commun. Eng. D-II (Japan);
vol.J75D-II, no.8;
Aug. 1992; pp. 1353-63
Abstract Introduces a method to create a hierarchical description of
smooth curved surfaces with scale-space analysis. The authors
extend the scale-space method used in 1D signal analysis to a 3D
surface. An object is described with two steps. In the first step,
a 3D scale-space images are segmented by zero-crossings of
curvatures at each scale and then linked between consecutive
scales based on topological changes (KH-description). In the
second step, the KH-description is parsed and translated into a
PS-tree which contains the number and distribution of regions
required for shape matching. The multiresolution hierarchical
description contains coarse-to-fine shape information of the
object, and examples show that the PS-tree symbolic description
is suitable for efficient coarse-to-fine 3D shape matching. The
effectiveness of this approach is demonstrated for raw data
derived from a range finder
Thesaurus feature extraction; image segmentation; topology; trees
(mathematics)
Other Terms 3D image segmentation; smooth curved surfaces; scale-space
analysis; zero-crossings; curvatures; topological changes; KH-
description; PS-tree; shape matching; multiresolution
hierarchical description; coarse-to-fine shape information;
symbolic description; range finder
ClassCodes C1250
Article Type Theoretical / Mathematical
Coden DTGDE7
Language Japanese
RecordType Journal
ControlNo. 4317321
AbstractNos. C9302-1250-173
References 13
Country Pub. Japan
date 1204
------------------------------------------------------------
Author Neumann, H.; Ottenberg, K.;
Fachbereich Inf., Hamburg Univ., Germany
Title Estimating attributes of smooth signal transitions from scale-
space
Source Proceedings. 11th IAPR International Conference on Pattern
Recognition. Vol.III. Conference C: Image, Speech and Signal
Analysis; Part: The Hague, Netherlands; Part: 30 Aug.-3 Sept.
1992;
Sponsored by: Int. Assoc Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xxv+791;
1992; pp. 754-8
Abstract Step-edge models as they have been used to model local intensity
variation, only rarely are justified for the real case of image
data. Due to finite apertures, the nature of scene geometry as
well as discretization of the image, local intensity variations
result in smooth transitions of varying width and local contrast.
In order to appropriately deal with the robust detection and
localization of image contrast, the authors propose the
parametrized ramp transition as local signal model. The scale-
space processing scheme for token extraction consists of a
cascade of first band-pass filtering the raw data and a
subsequent correlation of the result with a scaled first order
derivative operator. The robust contrast detection within scale
space and the estimation of local signal attributes in closed
form is documented. The scheme can be extended to deal with
intensity variations of different specificity
Thesaurus edge detection; filtering and prediction theory
Other Terms edge detection; smooth signal transitions; scale-space;
parametrized ramp transition; local signal model; token
extraction; first band-pass filtering; robust contrast detection
; signal attributes; intensity variations
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4311076
AbstractNos. B9302-6140C-129; C9302-1250-120
ISBN or SBN 0 8186 2920 7
References 12
Country Pub. USA
date 1204
------------------------------------------------------------
Author Kin, G.; Sato, M.;
Precision & Intelligence Lab., Tokyo Inst. of Technol., Yokohama,
Japan
Title Scale space filtering on spherical pattern
Source Proceedings. 11th IAPR International Conference on Pattern
Recognition. Vol.III. Conference C: Image, Speech and Signal
Analysis; Part: The Hague, Netherlands; Part: 30 Aug.-3 Sept.
1992;
Sponsored by: Int. Assoc Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xxv+791;
1992; pp. 638-41
Abstract For pattern information processing like recognition or
understanding, one must express the given pattern properly for
later processing. Many ways have been developed to express the
hierarchy of a pattern, but many of them use one dimensional or
two dimensional patterns. It is important to find an expression
reflecting the hierarchical structure of a spherical pattern. In
this paper, the authors propose the scale space filtering on a
spherical pattern to express its hierarchy
Thesaurus filtering and prediction theory; image recognition
Other Terms 1D pattern; 2D pattern; Gaussian kernel; image recognition;
convolution; spherical pattern; hierarchical structure; scale
space filtering
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4311048
AbstractNos. B9302-6140C-106; C9302-1250-098
ISBN or SBN 0 8186 2920 7
References 3
Country Pub. USA
date 1204
------------------------------------------------------------
Author Neumann, H.; Ottenberg, K.; Stiehl, H.S.;
Fachbereich Inf., Hamburg Univ., Germany
Title Finding and describing local structure in discrete two-
dimensional computed tomograms
Source Proceedings. 11th IAPR International Conference on Pattern
Recognition. Vol.III. Conference C: Image, Speech and Signal
Analysis; Part: The Hague, Netherlands; Part: 30 Aug.-3 Sept.
1992;
Sponsored by: Int. Assoc Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xxv+791;
1992; pp. 408-12
Abstract Differently scaled intensity discontinuities along the gradient
direction of scaled oriented contrast edges define significant X-
ray CT and MR image structures. Reliable detection and
quantitative description of such scaled intensity discontinuities
is achieved with a scale-space approach. It results in an
explicit token representation which can be understood as a
compact symbolic description of significant image structure,
namely a set of quantitative attributes per contrast edge.
Moreover, a multi-resolution approach is used to reconstruct the
image intensity function from the token representation alone
using a membrane as prior image model. Current results from the
novel entire processing cascade, which combines a quantitative
discontinuity description and a membrane-based intensity
reconstruction, are presented
Thesaurus biomedical NMR; computerised tomography; edge detection; image
reconstruction; medical diagnostic computing
Other Terms 2D discrete computerised tomography; local structure description;
edge detection; multiple resolution; image intensity function
reconstruction; computed tomograms; X-ray CT; MR image
structures; scaled intensity discontinuities; scale-space;
explicit token representation; symbolic description; prior
image model; membrane-based intensity reconstruction
ClassCodes A8760G; A8760J; A8770E; C7330; C5260B; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4310991
AbstractNos. A9303-8760G-009; C9302-7330-021
ISBN or SBN 0 8186 2920 7
References 14
Country Pub. USA
date 1204
------------------------------------------------------------
Author van den Boomgaard, R.; Smeulders, A.W.M.;
Fac. of Math. & Comput. Sci., Amsterdam Univ., Netherlands
Title The morphological structure of images
Source Proceedings. 11th IAPR International Conference on Pattern
Recognition. Vol.III. Conference C: Image, Speech and Signal
Analysis; Part: The Hague, Netherlands; Part: 30 Aug.-3 Sept.
1992;
Sponsored by: Int. Assoc Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xxv+791;
1992; pp. 268-71
Abstract The authors investigate the use of mathematical morphology to
construct scale-spaces. These scale-spaces are based on
differential equations, which are solved by morphological
operators, describing the evolution of images in scale-space
Thesaurus differential equations; image processing; mathematical
morphology
Other Terms image processing; morphological structure; mathematical
morphology; differential equations; scale-space
ClassCodes B6140C; B0220; C1250; C1120
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4304622
AbstractNos. B9301-6140C-360; C9301-1250-322
ISBN or SBN 0 8186 2920 7
References 10
Country Pub. USA
date 1204
------------------------------------------------------------
Author Jackway, P.T.;
Centre for Signal Process. Res., Queensland Univ. of Technol.,
Brisbane, Qld., Australia
Title Morphological scale-space
Source Proceedings. 11th IAPR International Conference on Pattern
Recognition. Vol.III. Conference C: Image, Speech and Signal
Analysis; Part: The Hague, Netherlands; Part: 30 Aug.-3 Sept.
1992;
Sponsored by: Int. Assoc Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xxv+791;
1992; pp. 252-5
Abstract Scale-space is an important recent concept used in image
processing and pattern recognition. Traditional scale-space is
generated by a linear smoothing operation. The author presents a
nonlinear type of smoother related to mathematical morphology
which meets (modified) 'scale-space axioms' and also generates a
'scale-space'. This scale-space is full-plane and preserves the
positions of features
Thesaurus filtering and prediction theory; image processing; image
recognition; mathematical morphology
Other Terms nonlinear smoothing; morphological scale space; image processing
; pattern recognition; mathematical morphology
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4304618
AbstractNos. B9301-6140C-356; C9301-1250-318
ISBN or SBN 0 8186 2920 7
References 10
Country Pub. USA
date 1204
------------------------------------------------------------
Author Fermuller, C.; Kropatsch, W.;
Center for Autom. Res., Maryland Univ., College Park, MD, USA
Title Hierarchical curve representation
Source Proceedings. 11th IAPR International Conference on Pattern
Recognition. Vol.III. Conference C: Image, Speech and Signal
Analysis; Part: The Hague, Netherlands; Part: 30 Aug.-3 Sept.
1992;
Sponsored by: Int. Assoc Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xxv+791;
1992; pp. 143-6
Abstract Presents a robust method for describing planar curves in multiple
resolution using curvature information. The method is developed
by taking into account the discrete nature of digital images as
well as the discrete aspect of a multiresolution structure
(pyramid). The authors deal with the robustness of the technique,
which is due to the additional information that is extracted from
observing the behavior of corners in the pyramid. Furthermore the
resulting algorithm is conceptually simple and easily
parallelizable. They develop theoretical results, analyzing the
curvature of continuous curves in scale-space, which show the
behavior of curvature extrema under varying scale. These results
are used to eliminate any ambiguities that might arise from
sampling problems due to the discreteness of the representation.
Finally, experimental results demonstrate the potential of the
method
Thesaurus feature extraction; image processing; image recognition
Other Terms hierarchical curve representation; image recognition; feature
extraction; planar curves; digital images; multiresolution
structure; pyramid; curvature; continuous curves
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4304592
AbstractNos. B9301-6140C-335; C9301-1250-299
ISBN or SBN 0 8186 2920 7
References 4
Country Pub. USA
date 1204
------------------------------------------------------------
Author Kok, T.C.W.;
Dept. of Electron. Eng., City Polytech. of Hong Kong, Kowloon
Tong, Hong Kong
Title Multiresolution image segmentation
Source Computer, Communication and Networking Systems: An Integrated
Perspective. Proceedings of the International Conference on
Information Engineering - ICIE '91; Part: Singapore; Part: 2-5
Dec. 1991;
Amsterdam, Netherlands;
Elsevier;
2 vol. xvi+1008;
1992; pp. 65-70 vol.1
Editor Subramanian, K.R.; Seumahu, E.S.
Abstract This paper presents a novel segmentation technique based on
dynamic thresholding using multiresolution images. A threshold
surface is constructed by local segmentation across the
multiresolution images formed by scale space filtering to adapt
itself to learn the varying illumination from the image. Computer
simulation is presented, and it shows promising results of the
proposed technique
Thesaurus digital simulation; image processing
Other Terms segmentation technique; dynamic thresholding; multiresolution
images; scale space filtering; illumination
ClassCodes B6140C; C5260B; C6185
Article Type Practical
Language English
RecordType Conference
ControlNo. 4292148
AbstractNos. B9301-6140C-097; C9301-5260B-074
ISBN or SBN 0 444 89480 2
References 10
Country Pub. Netherlands
date 1195
------------------------------------------------------------
------------------------------------------------------------
Author Rangarajan, K.; Allen, W.; Shah, M.;
Dept. of Comput. Sci., Central Florida, Orlando, FL, USA
Title Recognition using motion and shape
Source Proceedings. 11th IAPR International Conference on Pattern
Recognition. Vol.1. Conference A: Computer Vision and Applications
; Part: The Hague, Netherlands; Part: 30 Aug.-3 Sept. 1992;
Sponsored by: Int. Assoc. Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xxv+795;
1992; pp. 255-8
Abstract Presents a method for matching sets of trajectories which
supplements motion information with knowledge about the spatial
relationships between points on the moving object. First the
authors present a simple algorithm which matches two single
trajectories using only motion information. They convert the 2D
motion trajectories into two 1D signals based on the speed and
direction components. The signals are then represented by scale-
space images both to simplify matching and because the scale-
space representations are translation and rotation invariant.
They extend the matching algorithm to include spatial information
and propose a second algorithm which matches multiple
trajectories by combining motion and spatial match scores. Both
algorithms were tested with real and synthetic data
Thesaurus pattern recognition
Other Terms 2D trajectory matching; shape information; pattern recognition;
motion information; 2D motion trajectories; scale-space images;
spatial information
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4286652
AbstractNos. B9301-6140C-060; C9301-1250-041
ISBN or SBN 0 8186 2910 X
References 9
Country Pub. USA
date 1204
------------------------------------------------------------
Author Morita, S.; Kawashima, T.; Aoki, Y.;
Fac. of Eng., Hokkaido Univ., Sapporo, Japan
Title Hierarchical shape recognition based on 3-D multiresolution
analysis
Source Computer Vision - ECCV '92. Second European Conference on
Computer Vision Proceedings; Part: Santa Margherita Ligure, Italy
; Part: 18-23 May 1992;
Berlin, Germany;
Springer-Verlag;
xv+909;
1992; pp. 843-51
Editor Sandini, G.
Abstract The paper introduces a method to create a hierarchical
description of smooth curved surfaces based on scale-space
analysis. The authors extend the scale-space method used in 1-D
signal analysis to 3-D object. A 3-D scale-space images are
segmented by zero-crossings of surface curvatures at each scale
and then linked between consecutive scales based on topological
changes (KH-description). The KH-description is, then, parsed and
translated into the PS-tree which contains the number and
distribution of subregions required for shape matching. The KH-
description contains coarse-to-fine shape information of the
object and the PS-tree is suitable for shape matching. A
hierarchical matching algorithm using the descriptions is
proposed and examples show that the symbolic description is
suitable for efficient coarse-to-fine 3-D shape matching
Thesaurus computer vision; image processing; pattern recognition
Other Terms 3D objects; 3D multiresolution analysis; scale-space filtering;
smooth curved surfaces; scale-space analysis; surface
curvatures; topological changes; KH-description; PS-tree;
shape matching; hierarchical matching algorithm; symbolic
description
ClassCodes B6140C; C5260B; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4286538
AbstractNos. B9301-6140C-051; C9301-5260B-041
ISBN or SBN 3 540 55426 2
References 10
Country Pub. Germany
date 1201
------------------------------------------------------------
Author Brunnstrom, K.; Lindeberg, T.; Eklundh, J.-O.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title Active detection and classification of junctions by foveation
with a head-eye system guided by the scale-space primal sketch
Source Computer Vision - ECCV '92. Second European Conference on
Computer Vision Proceedings; Part: Santa Margherita Ligure, Italy
; Part: 18-23 May 1992;
Berlin, Germany;
Springer-Verlag;
xv+909;
1992; pp. 701-9
Editor Sandini, G.
Abstract The authors consider how junction detection and classification
can be performed in an active visual system. This is to
demonstrate that feature detection and classification in general
can be done by both simple and robust methods, if the vision
system is allowed to look at the world rather than at prerecorded
images. The authors address the issue of how to attract attention
to salient local image structures, as well as how to characterize
them
Thesaurus computer vision; pattern recognition
Other Terms region of interest determination; foveation; head-eye system;
scale-space primal sketch; junction detection; active visual
system; feature detection; local image structures
ClassCodes B6140C; C5260B; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4286518
AbstractNos. B9301-6140C-036; C9301-5260B-027
ISBN or SBN 3 540 55426 2
References 19
Country Pub. Germany
date 1201
------------------------------------------------------------
Author Florack, L.M.J.; ter Haar Romeny, B.M.; Koenderink, J.J.;
Viergever, M.A.;
Univ. Hospital, Utrecht, Netherlands
Title Families of tuned scale-space kernels
Source Computer Vision - ECCV '92. Second European Conference on
Computer Vision Proceedings; Part: Santa Margherita Ligure, Italy
; Part: 18-23 May 1992;
Berlin, Germany;
Springer-Verlag;
xv+909;
1992; pp. 19-23
Editor Sandini, G.
Abstract The authors propose a formalism for deriving parametrised
ensembles of local neighbourhood operators on the basis of a
complete family of scale-space kernels, which are apt for the
measurement of a specific physical observable. The parameters are
introduced in order to associate a continuum of a priori
equivalent kernels with each scale-space kernel, each of which is
tuned to a particular parameter value. Ensemble averages, or
other functional operations in parameter space, may provide
robust information about the physical observable of interest. The
approach gives a possible handle on incorporating multi-
valuedness (transparency) and visual coherence into a single
model. The authors consider the case of velocity tuning to
illustrate the method. The emphasis, however, is on the formalism,
which is more generally applicable
Thesaurus computer vision; digital filters; filtering and prediction
theory; picture processing
Other Terms filter tuning; local neighbourhood operators; scale-space
kernels; functional operations; parameter space; physical
observable; multi-valuedness; transparency; visual coherence;
velocity tuning
ClassCodes B6140C; C5260B; C1250; C5240
Article Type Practical
Language English
RecordType Conference
ControlNo. 4281795
AbstractNos. B9212-6140C-225; C9212-5260B-133
ISBN or SBN 3 540 55426 2
References 18
Country Pub. Germany
date 1201
------------------------------------------------------------
Author Toth, C.K.; Schenk, T.;
Dept. of Geodetic Sci. & Surveying, Ohio State Univ., Columbus,
OH, USA
Title Feature-based matching for automatic image registration
Source ITC Journal;
ITC J. (Netherlands);
no.1;
1992; pp. 40-6
Abstract For merging information extracted from satellite images with a
GIS, the images are usually registered on a map by manually
identifying a number of points on the satellite image, whose
coordinates are measured on the map. The authors describe a
method to solve the registration problem automatically. First,
the authors develop a general scheme to extract features (edges)
in the image and to match them with the corresponding features on
the map. The authors take advantage of the multi-spectral
resolution of the satellite image to perform the matching with
selective features, for example with water bodies, cultural
features or roads. A scale space approach is chosen for solving
the problem of vastly different image scales. The paper concludes
with experimental results
Thesaurus computerised pattern recognition; computerised picture processing
; geographic information systems; remote sensing
Other Terms feature extraction; edge extraction; computerised pattern
recognition; remote sensing; feature-based mapping;
computerised picture processing; automatic image registration;
satellite images; GIS; multi-spectral resolution; water bodies;
cultural features; roads; scale space approach
ClassCodes C7840; C5260B
Article Type Practical; Experimental
Coden ITCJDP
Language English
RecordType Journal
ControlNo. 4277205
AbstractNos. C9212-7840-079
ISSN 03032434
References 7
Country Pub. Netherlands
date 1197
------------------------------------------------------------
Author Eggert, D.W.; Bowyer, K.W.; Dyer, C.R.; Christensen, H.I.;
Goldgof, D.B.;
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL,
USA
Title Applying the scale space concept to perspective projection aspect
graphs
Source Theory and Applications of Image Analysis. Selected Papers from
the 7th Scandinavian Conference; Part: Aalborg, Denmark; Part:
13-16 Aug. 1991;
Singapore;
World Scientific;
xiii+346;
1992; pp. 48-62
Editor Johansen, P.; Olsen, S.
Abstract This paper reviews a complete implementation of an algorithm to
compute the exact aspect graph of solids of revolution under
perspective projection in 3-D space. The authors explore the
notion of introducing scale into the qualitative aspect graph
framework, thus providing a mechanism for selecting a level of
detail that is 'large enough' to merit explicit representation.
Several alternative interpretations of the scale space aspect
graph are examined in response to the results produced for an
example object by the implemented system
Thesaurus graph theory; picture processing
Other Terms perspective projection aspect graphs; algorithm; solids of
revolution; explicit representation; scale space aspect graph
ClassCodes B6140C; B0250; C1250; C1160
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4270048
AbstractNos. B9212-6140C-105; C9212-1250-078
ISBN or SBN 981 02 0945 2
References 36
Country Pub. Singapore
date 1191
------------------------------------------------------------
Author Lindeberg, T.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title On the behaviour in scale-space of local extrema and blobs
Source Theory and Applications of Image Analysis. Selected Papers from
the 7th Scandinavian Conference; Part: Aalborg, Denmark; Part:
13-16 Aug. 1991;
Singapore;
World Scientific;
xiii+346;
1992; pp. 38-47
Editor Johansen, P.; Olsen, S.
Abstract Elementary techniques from real analysis and singularity theory
are applied to derive analytical results for the behaviour in
scale-space of critical points and related entities. The main
results of the treatment comprise a description of the general
nature of trajectories of critical points in scale-space, an
estimation of the drift velocity of critical points and edges, an
analysis of the qualitative behaviour of critical points in
bifurcation situations, and a classification of types of blob
bifurcations possible
Thesaurus critical points; picture processing
Other Terms image analysis; scale-space; local extrema; singularity theory;
critical points; trajectories; drift velocity; blob
bifurcations
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4270047
AbstractNos. B9212-6140C-104; C9212-1250-077
ISBN or SBN 981 02 0945 2
References 17
Country Pub. Singapore
date 1191
------------------------------------------------------------
Author ter Haar Romeny, B.M.; Florack, L.M.J.; Koenderink, J.J.;
Viergever, M.A.;
Comput. Vision Res. Group, Utrecht Univ. Hospital, Netherlands
Title Invariant third order properties of isophotes: T-junction
detection
Source Theory and Applications of Image Analysis. Selected Papers from
the 7th Scandinavian Conference; Part: Aalborg, Denmark; Part:
13-16 Aug. 1991;
Singapore;
World Scientific;
xiii+346;
1992; pp. 30-7
Editor Johansen, P.; Olsen, S.
Abstract Geometric properties of isophotes are essential elements in image
analysis techniques, due to their invariance under general
invertible intensity transformations. The authors consider
geometric properties which in addition are to be invariant under
the group of rotations in the image domain. The third order local
properties of isophotes are studied by a scale space approach.
Numerical differentiation is replaced by convolution with
Gaussian derivatives, to study higher order geometrical
properties and to make a robust computer implementation.
Isophotes at different intensity levels show a large change in
curvature at T-junctions over a relatively small spatial scale,
so that the gradient of isophote curvature is a good candidate
for a T-junction detector
Thesaurus picture processing
Other Terms isophotes; image analysis; invertible intensity transformations;
third order local properties; scale space approach;
convolution; curvature; T-junction detector
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4270046
AbstractNos. B9212-6140C-103; C9212-1250-076
ISBN or SBN 981 02 0945 2
References 15
Country Pub. Singapore
date 1191
------------------------------------------------------------
Author Kawamata, M.; Kanbara, H.; Higuchi, T.;
Dept. of Electron. Eng., Fac. of Eng., Tohoku Univ., Sendai, Japan
Title Determination of IFS codes using scale-space correlation
functions (iterated function systems)
Source Workshop Notes. 1992 IEEE International Workshop on Intelligent
Signal Processing and Communication Systems; Part: Taipei, Taiwan
; Part: 19-21 March 1992;
Sponsored by: IEEE;
Taipei, Taiwan;
Nat. Taiwan Univ;
xvii+603;
1992; pp. 219-33
Abstract Iterated function systems are regarded as time-variant state-
space digital filters. IFS codes are obtained by determination of
the numbers of contractive affine transformations and of their
coefficients. Scale-space autocorrelation functions and
coefficients are defined to determine coefficients of each
contractive affine transformation. The important properties of
these functions are proved for the determination of IFS codes.
Coefficients of the contractive affine transformations can be
determined from coordinates which maximize scale-space
autocorrelation functions and coefficients of fractal images.
Scale-space filtering is introduced in order to determine the
number of affine transformations. First order zero-crossings are
used to obtain a hierarchic description of scale-space images,
which is a sequence of scale-space filtered images. This paper
proposes an algorithm to determine IFS codes, and gives an
illustrative example
Thesaurus codes; correlation methods; data compression; digital filters;
filtering and prediction theory; fractals; state-space methods
Other Terms iterated function system codes; scale-space correlation functions
; time-variant state-space digital filters; contractive affine
transformations; fractal images; zero-crossings; hierarchic
description; scale-space filtered images; algorithm
ClassCodes B6140C; B6120B; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4260247
AbstractNos. B9211-6140C-228; C9211-1250-178
References 6
Country Pub. Taiwan
date 1199
------------------------------------------------------------
Author Lindeberg, T.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title Scale-space behaviour of local extrema and blobs
Source Journal of Mathematical Imaging and Vision;
J. Math. Imaging Vis. (Netherlands);
vol.1, no.1;
March 1992; pp. 65-99
Abstract Elementary techniques from real analysis, and singularity theory,
are applied to derive analytical results for the behaviour in
scale-space of critical points and related entities. The main
results of the treatment comprise a description of the general
nature of trajectories of critical points in scale-space,
estimates of the drift velocity of critical points and straight
edges, an analysis of the qualitative behaviour of critical
points in bifurcation situations, and a classification of what
types of blob events are possible
Thesaurus picture processing
Other Terms scale-space behaviour; local extrema; blobs; real analysis;
singularity theory; critical points; trajectories; drift
velocity; straight edges; bifurcation situations
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Journal
ControlNo. 4258520
AbstractNos. B9211-6140C-205; C9211-1250-164
ISSN 09249907
References 31
Country Pub. Netherlands
date 1199
------------------------------------------------------------
Author Mokhtarian, F.; Mackworth, A.K.;
NTT Basic Res. Lab., Tokyo, Japan
Title A theory of multiscale, curvature-based shape representation for
planar curves
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.14, no.8;
Aug. 1992; pp. 789-805
Abstract A shape representation technique suitable for tasks that call for
recognition of a noisy curve of arbitrary shape at an arbitrary
scale or orientation is presented. The method rests on the
describing a curve at varying levels of detail using features
that are invariant with respect to transformations that do not
change the shape of the curve. Three different ways of computing
the representation are described. They result in three different
representations: the curvature scale space image, the
renormalized curvature scale space image, and the resampled
curvature scale space image. The process of describing a curve at
increasing levels of abstraction is referred to as the evolution
or arc length evolution of that curve. Several evolution and arc
length evolution properties of planar curves are discussed
Thesaurus pattern recognition; picture processing
Other Terms multiscale curvature based shape representation; pattern
recognition; image processing; planar curves; curvature scale
space image; renormalized curvature scale space image;
resampled curvature scale space image; arc length evolution
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4246272
AbstractNos. B9211-6140C-069; C9211-1250-039
ISSN 01628828
References 39
U.S. Copyright Clearance Center Code
0162-8828/92/$03.00
Country Pub. USA
date 1204
------------------------------------------------------------
Author Freeman, M.O.; Duell, K.A.; Fedor, A.;
Nat. Sci. Found. Center for Optoelectron. Comput. Syst., Colorado
Univ., Boulder, CO, USA
Title Multi-scale optical image processing
Source 1991 IEEE International Sympoisum on Circuits and Systems (Cat.
No.91CH3006-4); Part: Singapore; Part: 11-14 June 1991;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
5 vol. xlviii+3177;
1991; pp. 2355-8 vol.4
Abstract The authors introduce two multiscale optical image processing
systems, a centroid scale-space processor and an optical wavelet
processor. A.P. Witkin (1984) introduced the idea of scale-space,
where information is presented on a coordinate system with
continuous spatial and scale axes. His representation consists of
a convolving the input signal with a Laplacian of a Gaussian
point spread function and retaining the zero-crossings (which
correspond to edges) as scale (width of the Gaussian) is varied.
These edge maps form continuous contours in scale-space. The
optical implementation of the system is discussed. The centroid
scale-space map (CSSM) is constructed. This technique is extended
to 2D input functions by using correlation techniques. The
optical system which computes a 2D wavelet transform is shown.
One special advantage is that the system complexity is
independent of the scale parameter. This gives the flexibility to
tailor the scale parameter to the particular application
Thesaurus optical information processing; picture processing
Other Terms spatial axes; multiscale optical image processing systems;
centroid scale-space processor; optical wavelet processor;
scale-space; coordinate system; scale axes; Gaussian point
spread function; zero-crossings; edge maps; continuous contours
; optical implementation; correlation techniques; 2D wavelet
transform; system complexity
ClassCodes B6140C; B4180; C5270; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4244516
AbstractNos. B9211-6140C-032; C9211-5270-005
ISBN or SBN 0 7803 0050 5
References 11
U.S. Copyright Clearance Center Code
CH3006-4/91/0000-2355$01.00
Country Pub. USA
date 1189
------------------------------------------------------------
Author Hattori, T.; Yamasaki, T.; Watanabe, Y.; Sanada, H.; Tezuka, Y.;
Inf. & Comput. Sci. Lab., Kagawa Univ., Takamatsu, Japan
Title Distance based vector field method for feature extraction of
characters and figures
Source Conference Proceedings 1991 IEEE International Conference on
Systems, Man, and Cybernetics. 'Decision Aiding for Complex
Systems (Cat. No.91CH3067-6); Part: Charlottesville, VA, USA; Par
t: 13-16 Oct. 1991;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
3 vol. xvi+2120;
1991; pp. 207-12 vol.1
Abstract A new method is proposed for feature extraction and
representation of character and figure patterns using a vector
field. The vector field is constructed from a distance
transformation like the gradient vector of the electric field
caused by a charged pattern. Features are defined by a set of the
source points, sink points, and locally homogeneous domains of
the vector field. It is shown that these features are effective
for detecting holes (loops) and directional segments of the input
pattern. The pattern and the frame can be segmented naturally and
the segmentation represents the juxtapositional relation among
the locally homogeneous domains of flow-out vectors from the
pattern. The authors discuss the relation between the distance
transformation that the vector field is based on and scale-space
filtering which can be regarded as a kind of diffusion and/or
blurring processing of the shape of pattern
Thesaurus character recognition; filtering and prediction theory; pattern
recognition
Other Terms character recognition; shape analysis; pattern recognition;
feature extraction; figure patterns; vector field; distance
transformation; segmentation; juxtapositional relation; scale-
space filtering
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4234255
AbstractNos. B9210-6140C-174; C9210-1250-138
ISBN or SBN 0 7803 0233 8
References 8
U.S. Copyright Clearance Center Code
0 7803 0233 8/91$01.00
Country Pub. USA
date 1193
------------------------------------------------------------
Author Fedor, A.; Freeman, M.O.;
Optoelectron. Comput. Syst. Center, Colorado Univ., Boulder, CO,
USA
Title Optical multiscale morphological processor using a complex-valued
kernel
Source Applied Optics;
Appl. Opt. (USA);
vol.31, no.20;
10 July 1992; pp. 4042-50
Abstract Morphological transformations are typically performed on binary
images by convolution with a binary kernel, which is followed by
a threshold. The authors present an alternate approach that uses
a complex-valued kernel with odd symmetry to perform these
morphological operations. The complex-valued kernel increases the
information-processing ability of the processor with no increase
in system complexity. One advantage is that the processor
operates on all constant regions of a gray-level image in
parallel. A scale-space representation of this processor is
obtained by varying the size of the kernel continuously through a
range of scales. By using redundant information in the scale
representation, this system is found to be robust in the presence
of noise and spatial nonuniformities in the image. An optical
system to perform morphological filtering based on this system is
presented
Thesaurus optical systems; picture processing; spatial filters
Other Terms optical image noise; image processing; multiscale morphological
processor; complex-valued kernel; binary images; convolution;
binary kernel; threshold; odd symmetry; information-processing
ability; system complexity; gray-level image; scale-space
representation; scale representation; spatial nonuniformities;
optical system; morphological filtering
ClassCodes A4230V; B6140C
Article Type Theoretical / Mathematical; Experimental
Coden APOPAI
Language English
RecordType Journal
ControlNo. 4230830
AbstractNos. A9220-4230-003; B9210-6140C-154
ISSN 00036935
References 23
U.S. Copyright Clearance Center Code
0003-6935/92/204042-09$05.00/0
Country Pub. USA
date 1203
------------------------------------------------------------
Author Florack, L.M.J.; ter Haar Romeny, B.M.; Koenderink, J.J.;
Viergever, M.A.;
Comput. Vision Res. Group, Utrecht Univ. Hospital, Netherlands
Title Scale and the differential structure of images
Source Image and Vision Computing;
Image Vis. Comput. (UK);
vol.10, no.6;
July-Aug. 1992; pp. 376-88
Abstract Scaled partial differential operators enable local image analysis
through the detection of local differential structure in a robust
way, while at the same time capturing global features through the
extra scale degree of freedom. The paper shows why the operations
of scaling and differentiation cannot be separated. This
framework permits one to construct in a systematic way multiscale,
cartesian differential invariants, i.e. true image descriptors
that exhibit manifest invariance with respect to a change of
cartesian coordinates. The scale-space operators closely resemble
the receptive field profiles found in mammalian front-end visual
systems
Thesaurus computerised picture processing
Other Terms scaled partial differential operators; differential structure;
local image analysis; local differential structure; global
features; scaling; differentiation; cartesian differential
invariants; true image descriptors; manifest invariance;
cartesian coordinates; scale-space operators; receptive field
profiles; mammalian front-end visual systems
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Coden IVCODK
Language English
RecordType Journal
ControlNo. 4219231
AbstractNos. B9210-6140C-024; C9210-1250-019
ISSN 02628856
References 31
U.S. Copyright Clearance Center Code
0262-8856/92/006376-13
Country Pub. UK
date 1203
------------------------------------------------------------
Author Goshtasby, A.;
Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL,
USA
Title Gaussian decomposition of two-dimensional shapes: a unified
representation for CAD and vision applications
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.25, no.5;
May 1992; pp. 463-72
Abstract A new parametric representation for two-dimensional (2D) shapes
is introduced using Gaussians as basis functions. In this
representation, to design a shape, the parameters of the
Gaussians are specified. To recognize a shape, the shape is
decomposed into Gaussians and the parameters of the Gaussians are
used as features. Methods to design free-form shapes in CAD
applications and recognize shapes in vision applications are
described using the proposed representation
Thesaurus CAD; computer graphics; computer vision; computerised pattern
recognition
Other Terms 2D shapes; Gaussian decomposition; computer vision; scale
space images; CAD; parametric representation
ClassCodes B6140C; C1250; C5260B; C6130B; C7400
Article Type Applications; New Development; Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 4197957
AbstractNos. B9209-6140C-015; C9209-1250-020
ISSN 00313203
References 51
U.S. Copyright Clearance Center Code
0031-3203/92/$5.00+.00
Country Pub. UK
date 1201
------------------------------------------------------------
Author Guo-Li Ao; Yu-Jun Cui; Izumi, M.; Fukunaga, K.;
Shanghai Teacher's Univ., China
Title Structural tree representation of outlines and its application to
object recognition
Source Transactions of the Institute of Electronics, Information and
Communication Engineers D-II;
Trans. Inst. Electron. Inf. Commun. Eng. D-II (Japan);
vol.J75D-II, no.3;
March 1992; pp. 481-9
Abstract Scale-space filtering has been discussed in order to represent
the waveforms in hierarchical forms. But in a special condition
there may be large difference between the shapes of its zero
crossing lines of second derivative even if the different between
the structures of waveforms is not large. In addition, in the
description of the second zero crossing lines by graphs (tree
structure) and vice versa. It is difficult to describe the
structure by tree structure of previous manner. To solve these
problems, the authors introduce an equivalent transformation
between tree structures and propose the similarity between tree
structures. It is shown that the matching between outline figures
of objects can be efficiently examined, and an application of the
scale space approach to object recognition is discussed
Thesaurus pattern recognition; picture processing; trees (mathematics)
Other Terms waveforms; hierarchical forms; zero crossing lines; second
derivative; graphs; tree structure; scale space approach;
object recognition
ClassCodes C1250; C1160
Article Type Practical
Coden DTGDE7
Language Japanese
RecordType Journal
ControlNo. 4192321
AbstractNos. C9208-1250-295
References 9
Country Pub. Japan
date 1199
------------------------------------------------------------
Author Jeong, H.; Kim, C.I.;
Dept. of Electr. Eng., Pohang Inst. of Sci. & Technol., South
Korea
Title Adaptive determination of filter scales for edge detection
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.14, no.5;
May 1992; pp. 579-85
Abstract The authors suggest a regularization method for determining
scales for edge detection adaptively for each site in the image
plane. Specifically, they extend the optimal filter concept of T.
Poggio et al. (1984) and the scale-space concept of A. Witkin
(1983) to an adaptive scale parameter. To avoid an ill-posed
feature synthesis problem, the scheme automatically finds optimal
scales adaptively for each pixel before detecting final edge maps.
The authors introduce an energy function defined as a functional
over continuous scale space. Natural constraints for edge
detection are incorporated into the energy function. To obtain a
set of optimal scales that can minimize the energy function, a
parallel relaxation algorithm is introduced. Experiments for
synthetic and natural scenes show the advantages of the algorithm.
In particular, it is shown that this system can detect both step
and diffuse edges while drastically filtering out the random noise
Thesaurus filtering and prediction theory; pattern recognition; picture
processing
Other Terms adaptive scale determination; filter scales; edge detection;
regularization method; optimal filter; adaptive scale parameter;
energy function; continuous scale space; parallel relaxation
algorithm
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4185381
AbstractNos. B9208-6140C-226; C9208-1250-228
ISSN 01628828
References 24
U.S. Copyright Clearance Center Code
0162-8828/92/$03.00
Country Pub. USA
date 1201
------------------------------------------------------------
Author Grosky, W.I.; Jiang, Z.;
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
Title A hierarchical approach to feature indexing
Source Image Storage and Retrieval Systems; Part: San Jose, CA, USA; Par
t: 13-14 Feb. 1992;
Sponsored by: SPIE; IS&T;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1662;
1992; pp. 9-20
Abstract The authors extend their previous approach to 2D shape indexing,
data-driven indexed hypotheses, to hierarchical features. It is
shown mathematically and experimentally that an index based on
hierarchical features is more computationally efficient than one
based on non-hierarchical features. Their approach addresses two
types of hierarchies: a multilevel approximation of the contours
of 2D objects and a three-level feature indexing system. The
approach can easily be extended to 3D objects. Occluded object
recognition should be based on local features. However, these
features may sometimes be lost due to changes of scale as well as
to occlusion. The first hierarchical mechanism is used to
complement the feature loss due to scale changes. It results in
multilevel approximations of the contours of objects using scale-
space approaches. This approach will also be beneficial when
there are few boundary points of maximal curvature so that
standard polygonal approximation schemes don't work very well.
The second hierarchical mechanism is to use sets of visible local
features to hypothesize the presence of objects. Verification of
the various hypotheses is done via normalization and boundary
template matching
Thesaurus computerised pattern recognition; database management systems;
indexing; information retrieval
Other Terms image databases; occluded object recognition; visual databases;
feature indexing; 2D shape indexing; data-driven indexed
hypotheses; hierarchical features; multilevel approximation;
contours; three-level feature indexing; feature loss; scale
changes; scale-space; visible local features; normalization;
boundary template matching
ClassCodes C6160S; C5260B
Article Type Practical; Experimental
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4184535
AbstractNos. C9208-6160S-005
ISSN 0277786X
References 18
U.S. Copyright Clearance Center Code
0 8194 0816 6/92/$4.00
Country Pub. USA
date 1198
------------------------------------------------------------
Author Radha, H.; Leonardi, R.; Vetterli, M.;
AT&T Bell Lab., Holmdel, NJ, USA
Title A multiresolution approach to binary tree representations of
images
Source ICASSP 91: 1991 International Conference on Acoustics, Speech and
Signal Processing (Cat. No.91CH2977-7); Part: Toronto, Ont.,
Canada; Part: 14-17 April 1991;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
5 vol. 3732;
1991; pp. 2653-6 vol.4
Abstract A multiresolution method for constructing a BSP (binary space
partitioning) tree is introduced. This approach derives a
hierarchy (pyramid) of scale-space images from the original image.
In this hierarchy, a BSP tree of an image is built from other
trees representing low-resolution images of the pyramid. A low-
resolution image BSP tree serves as an initial guess to construct
a higher-resolution image tree. Due to filtering when
constructing the pyramid, details are discarded. As a result, a
more robust segmentation is obtained. Moreover a significant
computational advantage is achieved
Thesaurus filtering and prediction theory; picture processing; trees
(mathematics)
Other Terms image segmentation; binary tree representations;
multiresolution method; binary space partitioning; scale-space
images; low-resolution images; higher-resolution image;
filtering
ClassCodes B6140C; B0250; C1250; C1160
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4183670
AbstractNos. B9208-6140C-185; C9208-1250-189
ISBN or SBN 0 7803 0003 3
References 7
U.S. Copyright Clearance Center Code
CH2977-7/91/0000-2653$01.00
Country Pub. USA
date 1187
------------------------------------------------------------
Author Tai-Yuen Cheng; Chung-Lin Huang;
Dept. of Electr. Eng., Nat. Tsing-Hua Univ., Hsin-Chu, Taiwan
Title Color images segmentation using scale space filter and Markov
random field
Source Intelligent Robots and Computer Vision X: Algorithms and
Techniques; Part: Boston, MA, USA; Part: 11-13 Nov. 1991;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1607;
1992; pp. 358-68
Abstract The paper presents a hybrid method that combines the scale space
filter (SSF) and Markov random field (MRF) for color image
segmentation. Using the scale space filter, the authors separate
the different scaled histogram to intervals corresponding to
peaks and valleys. The basic construction of MRF is a joint
probability given the original data. The original data is the
image that the authors obtained from the source and the result is
called the label image. Because the MRF needs the number of
segments before it converges to the global minimum, they exploit
the scale space filter to do coarse segmentation and then use MRF
to do fine segmentation of the images. Finally, they compare the
experimental results obtained from using SSF only, or combined
with MRF using iterated conditional mode (ICM), and Gibbs sampling
Thesaurus colour; Markov processes; pattern recognition; picture
processing
Other Terms scale space filter; Markov random field; color image
segmentation; joint probability; coarse segmentation; fine
segmentation; iterated conditional mode; Gibbs sampling
ClassCodes B6140C; C1250; C1260
Article Type Practical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4174950
AbstractNos. B9208-6140C-037; C9208-1250-036
ISSN 0277786X
References 11
U.S. Copyright Clearance Center Code
0 8194 0744 5/92/$4.00
Country Pub. USA
date 1194
------------------------------------------------------------
Author Matsopoulos, G.; Marshall, S.;
Strathclyde Univ., Glasgow, UK
Title A new morphological scale space operator
Source International Conference on Image Processing and its Applications
(Conf. Publ. No.354); Part: Maastricht, Netherlands; Part: 7-9
April 1992;
London, UK;
IEE;
xxiv+628;
1992; pp. 246-9
Abstract Considers the technique of scale space for a range of image
processing and computer vision applications. In the past both
linear and morphological approaches have been used to evaluate a
scale space description and it has been shown that morphological
techniques possess certain advantages including speed of
computation. However the existing morphological approaches
produce a non symmetrical output with respect to intrusions and
protrusions of a signal. The paper describes a new morphological
approach for scale space description which eliminates the above
problem and which therefore treats both signal intrusions and
protrusions equally. Also, a new property called the AVEC
property, related to scale space behaviour is defined
Thesaurus computer vision; computerised picture processing
Other Terms image processing; computer vision; morphological approach;
scale space; signal intrusions; protrusion; AVEC property;
scale space behaviour
ClassCodes C1250; C5260B
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4174157
AbstractNos. C9207-1250-219
ISBN or SBN 0 85296 543 5
References 5
Country Pub. UK
date 1200
------------------------------------------------------------
Author Forte, P.; Netherwood, P.; Barnwell, P.;
Kingston Polytech., Kingston upon Thames, UK
Title Spiral arc shape representation for automatic inspection of
surface mount assemblies
Source International Conference on Image Processing and its Applications
(Conf. Publ. No.354); Part: Maastricht, Netherlands; Part: 7-9
April 1992;
London, UK;
IEE;
xxiv+628;
1992; pp. 143-6
Abstract Describes an efficient technique for representing 2D shapes, by
approximating their contours with segments of spiral arcs. By
definition a spiral arc is one which exhibits monotone curvature
along the arc length, straight line segments and circular arcs
being special cases. The arc is specified by giving the position
of each endpoint, plus the orientation of the tangent to the arc
at each endpoint. For a straight line or circular arc this
information specifies the curve uniquely. For other arcs a
formula is given for generating an arc between the two points.
This formula minimizes the curvature of the arc subject to
various smoothness constraints. The generated arc may only
approximate the true contour to within a specified level of
tolerance, where the degree of tolerance constitutes a scale
space parameter
Thesaurus computerised picture processing
Other Terms shape representation; automatic inspection; surface mount
assemblies; 2D shapes; spiral arcs; monotone curvature;
tolerance; scale space parameter
ClassCodes C5260B
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4169499
AbstractNos. C9207-5260B-124
ISBN or SBN 0 85296 543 5
References 6
Country Pub. UK
date 1200
------------------------------------------------------------
Author Lu, Y.; Jain, R.C.;
Environ. Res. Inst. of Michigan, Ann Arbor, MI, USA
Title Reasoning about edges in scale space
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.14, no.4;
April 1992; pp. 450-68
Abstract Explores the role of reasoning in early vision processing. In
particular, the problem of detecting edges is addressed. The
authors do not try to develop another edge detector, but rather,
they study an edge detector rigorously to understand its behavior
well enough to formulate a reasoning process that allow appliance
of the detector judiciously to recover useful information. They
present a multiscale reasoning algorithm for edge recovery:
reasoning about edges in scale space (RESS). The knowledge in
RESS is acquired from the theory of edge behavior in scale space
and represented by a number of procedures. RESS recovers desired
edge curves through a number of reasoning processes on zero
crossing images at various scales. The knowledge of edge behavior
in scale space enables RESS to select proper scale parameters,
recover missing edges, eliminate noise or false edges, and
correct the locations of edges. A brief evaluation of RESS is
performed by comparing it with two well-known multistage edge
detection algorithms
Thesaurus computer vision; inference mechanisms; knowledge representation
Other Terms computer vision; knowledge representation; inference mechanisms;
noise elimination; edges; scale space; edge detector;
multiscale reasoning algorithm; edge recovery; edge behavior;
edge curves; zero crossing images
ClassCodes C5260B; C6170
Article Type Practical; Theoretical / Mathematical; Experimental
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4166328
AbstractNos. C9207-5260B-093
ISSN 01628828
References 38
U.S. Copyright Clearance Center Code
0162-8828/92/$03.00
Country Pub. USA
date 1200
------------------------------------------------------------
Author Rattarangsi, A.; Chin, R.T.;
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Title Scale-based detection of corners of planar curves
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.14, no.4;
April 1992; pp. 430-49
Abstract A technique for detecting and localizing corners of planar curves
is proposed. The technique is based on Gaussian scale space,
which consists of the maxima of absolute curvature of the
boundary function presented at all scales. The scale space of
isolated simple and double corners is first analyzed to
investigate the behavior of scale space due to smoothing and
interactions between two adjacent corners. The analysis shows
that the resulting scale space contains line patterns that either
persist, terminate, or merge with a neighboring line. Next, the
scale space is transformed into a tree that provides simple but
concise representation of corners at multiple scales. Finally, a
multiple-scale corner detection scheme is developed using a
coarse-to-fine tree parsing technique. The parsing scheme is
based on a stability criterion that states that the presence of a
corner must concur with a curvature maximum observable at a
majority of scales. Experiments were performed to show that the
scale space corner detector is reliable for objects with multiple-
size features and noisy boundaries and compares favorably with
other corner detectors tested
Thesaurus filtering and prediction theory; pattern recognition; picture
processing; trees (mathematics)
Other Terms pattern recognition; picture processing; scale-based corners
detection; planar curves; Gaussian scale space; maxima of
absolute curvature; boundary function; line patterns; tree;
multiple-scale corner detection; coarse-to-fine tree parsing
technique; stability criterion
ClassCodes B6140C; B0250; C1250; C1160
Article Type Theoretical / Mathematical; Experimental
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4166327
AbstractNos. B9207-6140C-173; C9207-1250-150
ISSN 01628828
References 22
U.S. Copyright Clearance Center Code
0162-8828/92/$03.00
Country Pub. USA
date 1200
------------------------------------------------------------
Author Saund, E.;
Dept. of Brain & Cognitive Sci., MIT, Cambridge, MA, USA
Title Putting knowledge into a visual shape representation
Source Artificial Intelligence;
Artif. Intell. (Netherlands);
vol.54, no.1-2;
March 1992; pp. 71-119
Abstract Shows how a representation for visual shape can be formulated to
employ knowledge about the geometrical structures common within
specific shape domains. In order to support a wide variety of
later visual processing tasks, the authors seek representations
making explicit many geometric properties and spatial
relationships redundantly and at many levels of abstraction. The
authors offer two specific computational tools: (1) By
maintaining shape tokens on a scale-space blackboard, information
about the relative locations and sizes of shape fragments such as
contours and regions can be manipulated symbolically, while the
pictorial organization inherent to a shape's spatial geometry is
preserved. (2) Through the device of dimensionality-reduction,
configurations of shape tokens can be interpreted in terms of
their membership within deformation classes; this provides
leverage in distinguishing shapes on the basis of subtle
variations reflecting deformations in their forms. Using these
tools, knowledge in a shape representation resides in a
vocabulary of shape descriptors naming constellations of shape
tokens in the scale-space blackboard. The approach is illustrated
through a computer implementation of a hierarchical shape
vocabulary designed to offer flexibility in supporting important
aspects of shape recognition and shape comparison in the two-
dimensional shape domain of the dorsal fins of fishes
Thesaurus artificial intelligence; knowledge representation; visual
perception
Other Terms visual shape representation; knowledge; geometrical structures;
geometric properties; spatial relationships; computational
tools; shape tokens; scale-space blackboard; shape fragments;
pictorial organization; dimensionality-reduction; deformation
classes; constellations; two-dimensional shape domain; dorsal
fins
ClassCodes C1230; C6170
Article Type Theoretical / Mathematical
Coden AINTBB
Language English
RecordType Journal
ControlNo. 4165157
AbstractNos. C9207-1230-042
ISSN 00043702
References 44
U.S. Copyright Clearance Center Code
0004-3702/92/$05.00
Country Pub. Netherlands
date 1199
------------------------------------------------------------
Author Topkar, V.A.; Sood, A.K.;
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Title Statistical analysis of scale-space (computer vision)
Source Signal Processing;
Signal Process. (Netherlands);
vol.26, no.3;
March 1992; pp. 307-34
Abstract The noise and clutter cause major problems in scale-space because
it involves taking higher derivatives. Statistical analysis of
the noise as it is reflected in the scale-space representation
and its effect on any algorithm based on this representation
poses an interesting topic of research. Scale-space
representation involves convolving the input with a smoothing
filter (typically Gaussian) of different resolutions and
detecting the primitives (typically the zero crossings of the
second derivative) to form the scale-space representation.
Statistical analysis of the scale-space is nontrivial because of
two reasons: (i) it involves a nonlinear operation, namely the
detection of zero crossings and (ii) the noise at different
scales is correlated. The authors prove theorems which give the
probabilities of zero-crossings in the output in the presence of
noise. The theorems are then applied to the case of Gaussian
smoothing. These probabilities can be used for a number of
applications such as performance analysis
Thesaurus computer vision; filtering and prediction theory; picture
processing; probability; statistical analysis
Other Terms statistical analysis; zero-crossings probability; computer
vision; noise; clutter; scale-space representation; smoothing
filter; Gaussian smoothing
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden SPRODR
Language English
RecordType Journal
ControlNo. 4159846
AbstractNos. B9207-6140C-081; C9207-1250-071
ISSN 01651684
References 35
U.S. Copyright Clearance Center Code
0165-1684/92/$05.00
Country Pub. Netherlands
date 1199
------------------------------------------------------------
Author Takamatsu, R.; Kimura, K.; Sato, M.; Kawarada, H.;
Tokyo Inst. of Technol., Yokohama, Japan
Title Pitch determination with scale space filtering
Source Bulletin of Precision and Intelligence Laboratory;
Bull. Precis. Intell. Lab. (Japan);
no.66;
Sept. 1991; pp. 1-7
Abstract In conventional methods of pitch determination based on short-
term analysis, the pitch frequency fluctuates according to frame
length and positioning. Furthermore, pitch frequency is averaged
in the frame. This paper introduces a new pitch determination
algorithm using scale space filtering. Scale-space filtering is a
multi-resolutional filtering method which expands a waveform into
a set of waveforms for multi-scale measurement. Its zero-
crossings naturally describe the hierarchical structure of the
waveform. In the method, frame length is decided by the structure
of the waveform and pitch frequency is directly derived from a
single pitch period. Therefore the fluctuations due to frame
length and positioning are diminished and the changes of pitch
frequency are accurately determined. The result of an experiment
with the weather forecast sentence shows that the method performs
quite well
Thesaurus filtering and prediction theory; speech analysis and processing
Other Terms scale space filtering; pitch determination; pitch frequency;
frame length; multi-resolutional filtering method; zero-
crossings; hierarchical structure; frame length; weather
forecast sentence
ClassCodes B6130; B6140
Article Type Theoretical / Mathematical
Language English
RecordType Journal
ControlNo. 4154089
AbstractNos. B9206-6130-071
ISSN 03857832
References 3
Country Pub. Japan
date 1192
------------------------------------------------------------
Author Doi, S.; Mori, K.; Takahashi, H.; Shimizu, E.; Matsuda, M.;
Nara Nat. Coll. of Technol., Yamatokoriyama, Japan
Title Parallel processing of the scale-space filtering using the
transputer
Source Applications of Transputers 3. Proceedings of the Third
International Conference on Applications of Transputers; Part:
Glasgow, UK; Part: 28-30 Aug. 1991;
Sponsored by: UK SERC/DTI Initiative on the Eng. Appl.
Transputers; IEEE; IEE; IOP; et al;
Amsterdam, Netherlands;
IOS;
821;
1991; pp. 571-6
Editor Durrani, T.S.; Sandham, W.A.; Soraghan, J.J.; Forbes, S.M.
Abstract Two types of parallel processing algorithms are proposed for the
high speed calculation of scale-space filtering using the
transputer. The parallel algorithm utilizing the scale axis
division formula is executed by assigning the calculation divided
by scale parameter to each transputer. In this algorithm, the
measuring results show that the execution time for calculation
has been reduced proportional to the number of transputers. In
the parallel algorithm utilizing the adaptive search formula,
each zero-cross point is found at the same time from the small
area in which the existence of each zero-cross point is suspected
Thesaurus computerised signal processing; filtering and prediction theory;
parallel algorithms
Other Terms parallel processing; scale-space filtering; transputer;
parallel processing algorithms; scale axis division formula;
adaptive search formula; zero-cross point
ClassCodes B6140; C1260; C4240P
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4144457
AbstractNos. B9206-6140-209; C9206-1260-154
References 7
Country Pub. Netherlands
date 1191
------------------------------------------------------------
Author Janssen, H.; Kopecz, J.;
Inst. for Neuroinformatics, Ruhr-Univ. of Bochum, Germany
Title Image recognition in hypercolumnar scale space by sparsely coded
associative memory
Source Artificial Neural Networks. Proceedings of the 1991 International
Conference. ICANN-91; Part: Espoo, Finland; Part: 24-28 June
1991;
Amsterdam, Netherlands;
North-Holland;
2 vol. xix+1819;
1991; pp. 1203-6 vol.2
Editor Kohonen, T.; Makisara, K.; Simula, O.; Kangas, J.
Abstract The authors propose a pattern recognition system based on an
architecture close to the one found in human visual cortex which
is called hypercolumns. They show that this discrete parametric
representation can be used to define a short range interaction to
make desirable information like edge continuation more explicit.
They also show how hypercolumnar representations can be sparsely
coded for usage in a very efficient associative memory
recognition system. They combine this system with a model for
coarse-to-fine search in hypercolumnar scale space thus gaining
translational invariance. In principle the application of such a
representation appears to be very well suited for data reduction
and pattern recognition processes and is part of a neural
instruction set
Thesaurus computerised pattern recognition; computerised picture processing
; content-addressable storage
Other Terms hypercolumnar scale space; sparsely coded associative memory;
pattern recognition; discrete parametric representation; short
range interaction; coarse-to-fine search; translational
invariance; data reduction; neural instruction set
ClassCodes C5340; C5260B; C1250
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4143967
AbstractNos. C9206-5340-023
ISBN or SBN 0 444 89178 1
References 8
Country Pub. Netherlands
date 1189
------------------------------------------------------------
Author Topkar, V.A.; Sood, A.K.; Kjell, B.;
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Title Object detection using contrast based scale-space
Source Proceedings 1991 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (91CH2983-5); Part: Maui, HI, USA;
Part: 3-6 June 1991;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Sco. Press;
xvi+761;
1991; pp. 700-1
Abstract The authors propose four scale-space object detection algorithms
for separating objects from the background. These algorithms do
not need thresholding at any of the scales. The different
algorithms are applicable to images with different noise and
clutter characteristics. Statistical analysis of the four
algorithms is conducted for noisy and cluttered backgrounds
Thesaurus pattern recognition; picture processing
Other Terms statistical analysis; edge focusing; contrast based scale-space;
scale-space object detection; noise; clutter characteristics
ClassCodes C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4137196
AbstractNos. C9206-1250-036
ISBN or SBN 0 8186 2148 6
References 3
U.S. Copyright Clearance Center Code
CH2983-5/91/0000-0700$01.00
Country Pub. USA
date 1189
------------------------------------------------------------
Author Kulkarni, D.; Kutulakos, K.; Robinson, P.;
NASA Ames Res. Center, Moffett Field, CA, USA
Title Data analysis using scale-space filtering and Bayesian
probabilistic reasoning (for differential thermal analysis)
Source Computers & Chemistry;
Comput. Chem. (UK);
vol.16, no.1;
Jan. 1992; pp. 15-23
Abstract Describes a program for the analysis of output curves from a
differential thermal analyzer (DTA). The program first extracts
probabilistic qualitative features from a DTA curve of a soil
sample, and then uses Bayesian probabilistic reasoning to infer
what minerals are present in the soil. It consists of a qualifier
module and a classifier module. The qualifier employs a simple
and efficient extension of scale-space filtering DTA data.
Ordinarily, when filtering operations are not highly accurate,
points can vanish from contours in the scale-space image. To
handle the problem of vanishing points, the authors' algorithm
uses perceptual organization heuristics to group the points into
lines. It then groups these lines into contours by using
additional heuristics. Probabilities are associated with these
contours using domain-specific correlations. A Bayes tree
classifier processes probabilistic features to infer the presence
of different minerals in the soil. The authors show
experimentally that using domain-specific correlations to infer
qualitative features, this algorithm outperforms a domain-
independent algorithm that does not
Thesaurus Bayes methods; chemistry computing; classification; data
analysis; filtering and prediction theory; geochemistry;
heuristic programming; inference mechanisms; minerals;
probability; soil; thermal analysis; trees (mathematics)
Other Terms data analysis; output curves analysis; scale-space filtering;
Bayesian probabilistic reasoning; differential thermal analyzer;
probabilistic qualitative features; soil; minerals; qualifier
module; classifier module; contours; vanishing points;
perceptual organization heuristics; lines; domain-specific
correlations; Bayes tree classifier
ClassCodes A0650; A0250; C7320; C1140Z; C1260; C7340; C1230
Article Type Practical
Coden COCHDK
Language English
RecordType Journal
ControlNo. 4133272
AbstractNos. A9211-0650-001; C9206-7320-003
ISSN 00978485
References 12
U.S. Copyright Clearance Center Code
0097-8485/92/$5.00+0.00
Country Pub. UK
date 1197
------------------------------------------------------------
Author Jager, F.; Koren, I.; Gyergyek, L.;
Fac. of Electr. & Comput. Eng., Ljubljana, Yugoslavia
Title Multiresolution representation and analysis of ECG waveforms
Source Proceedings. Computers in Cardiology (Cat. No.90CH3011-4); Part:
Chicago, IL, USA; Part: 23-26 Sept. 1990;
Sponsored by: IEEE; Illinois Inst. Technol.; Pritzker Inst. Med.
Eng.; Nat. Inst. Health.; American Heart Assoc. of Metropolitan
Chicago; et al;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xxii+711;
1991; pp. 547-50
Abstract A new pattern recognition method is introduced for the
multiresolution representation and analysis of electrocardiogram
(ECG) waveforms. The multiresolution representation is based on
filtering the curvature of the curve with continuum of Gaussian
filters where Gaussian standard deviation increases, and on
extracting of extrema points in filtered versions of the
curvature (scale-space filtering). The original curve is then
segmented at each scale into linear parts with regard to the
extracted extrema points. After segmentation and linking segments
between scales, shape is represented qualitatively in a
hierarchical tree form holding information on coarser and finer
details of shape. Different methods of tree form analysis can be
applied to data compression, classification of heart beats or
fine structure analysis. The fast computation scheme and
transformation into hierarchical structure are described. In
addition to the method of representation, a data compression
method is proposed. Comparison to the AZTEC data compression
method is given
Thesaurus electrocardiography; pattern recognition; waveform analysis
Other Terms heart beats classification; curvature filtering; ECG waveforms
analysis; pattern recognition method; multiresolution
representation; Gaussian standard deviation; scale-space
filtering; extrema points; hierarchical tree form;
hierarchical structure; AZTEC data compression method
ClassCodes A8770E; A8730C; A8728; B7510D
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4127861
AbstractNos. A9210-8770E-023; B9205-7510D-049
ISBN or SBN 0 8186 2225 3
References 6
U.S. Copyright Clearance Center Code
0276-6574/91/0000-0547$01.00
Country Pub. USA
date 1179
------------------------------------------------------------
Author Sato, J.; Sato, M.;
Precision Intelligence Lab., Tokyo Inst. of Technol., Yokohama,
Japan
Title A local structural analysis of images based on scale space
filtering
Source Transactions of the Institute of Electronics, Information and
Communication Engineers D-II;
Trans. Inst. Electron. Inf. Commun. Eng. D-II (Japan);
vol.J74D-II, no.12;
Dec. 1991; pp. 1715-22
Abstract To realize artificial vision it is one of the important themes to
establish a good representation of pattern images for recognition
and understanding. We humans look at something hierarchically. We
see it to know its rough structure at first, then we view it to
understand its details. Scale space filtering is the operation of
convoluting a pattern image with the Gaussian blurring function,
which is an effective method to handle images hierarchically. In
this study, the authors analyze how the figure of ridge-valley
lines of the tone level of the image changes near the singular
stationary points locally. As a result of the analysis, they find
that the singular stationary points are classified into three
basic types, that is hyperbolic type, positive elliptic type, and
negative elliptic type
Thesaurus computer vision
Other Terms image representation; pattern recognition; pattern understanding
; convolution; hierarchical method; local structural analysis;
scale space filtering; artificial vision; rough structure;
details; Gaussian blurring function; ridge-valley lines; tone
level; singular stationary points; hyperbolic type; positive
elliptic type; negative elliptic type
ClassCodes C1250
Article Type Theoretical / Mathematical
Coden DTGDE7
Language Japanese
RecordType Journal
ControlNo. 4125406
AbstractNos. C9205-1250-060
References 7
Country Pub. Japan
date 1195
------------------------------------------------------------
Author Etoh, M.; Tomono, A.; Kishino, F.;
ATR Commun. Syst. Res. Labs., Kyoto, Japan
Title Stereo-based description by generalized cylinder complexes from
occluding contours
Source Systems and Computers in Japan;
Syst. Comput. Jpn. (USA);
vol.22, no.12;
1991; pp. 79-89
Abstract The paper proposes a stereo-based description technique as a
preprocessing step for three-dimensional (3-D) recognition of an
object representable by a straight homogeneous generalized
cylinder (SHGC). The 3-D position estimate of the SHGC model be
computed if the object being modeled is either a solid of
revolution or a body whose contour is symmetrical with respect to
its axial. The proposed algorithm is applicable to a complex
object if that object can be partitioned into a set of multiple
SHGCs. The most important task of the algorithm is the extraction
of a symmetry axis for each GC section of the object. The contour
lines are analyzed in a scale space. The analysis is performed
recursively to obtain each CC section that has stable contour
lines. The effectiveness of the proposed algorithm for 3-D
description of an object has been demonstrated via experimentation
Thesaurus pattern recognition; picture processing
Other Terms 3D object recognition; stereo imaging; generalized cylinder
complexes; occluding contours; stereo-based description; solid
of revolution; symmetry axis; GC section; contour lines;
stable contour lines
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden SCJAEP
Language English
RecordType Journal
ControlNo. 4115131
AbstractNos. B9205-6140C-032; C9205-1250-023
ISSN 08821666
References 19
U.S. Copyright Clearance Center Code
0882-1666/91/0012-0079$7.50/0
Country Pub. USA
date 1184
------------------------------------------------------------
Author Lindeberg, T.; Eklundh, J.O.;
Comput. Vision & Active Perception Lab., R. Inst. of Technol.,
Stockholm, Sweden
Title Scale detection and region extraction from a scale-space primal
sketch
Source Proceedings. Third International Conference on Computer Vision
(Cat. No.90CH2934-8); Part: Osaka, Japan; Part: 4-7 Dec. 1990;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xv+759;
1990; pp. 416-26
Abstract The authors present: (1) a multi-scale representation of gray-
level shape, called a scale-space primal sketch, which makes
explicit both features in scale-space and the relations between
features at different levels of scales; (2) a theory for
extraction of significant image structure from this
representation; and (3) applications to edge detection, histogram
analysis and junction classification demonstrating how the
proposed method can be used for guiding later stage processing.
The representation gives a qualitative description of the image
structure that allows for detection of stable scales and regions
of interest in a solely bottom-up data-driven way. In other words,
it generates coarse segmentation cues and can be hence seen as
preceding further processing, which can then be properly tuned.
The authors argue that once such information is available many
other processing tasks can become much simpler. Experiments on
real imagery demonstrate that the proposed theory gives
perceptually intuitive results
Thesaurus computer vision; computerised pattern recognition; computerised
picture processing
Other Terms scale detection; region extraction; scale-space primal sketch;
multi-scale representation; gray-level shape; features;
extraction of significant image structure; edge detection;
histogram analysis; junction classification; qualitative
description; coarse segmentation cues; real imagery
ClassCodes B6140C; C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4111561
AbstractNos. B9204-6140C-203; C9204-1250-222
ISBN or SBN 0 8186 2057 9
References 30
U.S. Copyright Clearance Center Code
CH2934-8/90/0000-0416$01.00
Country Pub. USA
date 1182
------------------------------------------------------------
Author Whitten, G.;
Fairchild Weston Syst. Inc., Syosset, NY, USA
Title A framework for adaptive scale space tracking solutions to
problems in computational vision
Source Proceedings. Third International Conference on Computer Vision
(Cat. No.90CH2934-8); Part: Osaka, Japan; Part: 4-7 Dec. 1990;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xv+759;
1990; pp. 210-20
Abstract A unified framework is developed for efficiently solving a wide
range of computational vision problems by performing adaptive
scale space tracking (where a solution at a coarse resolution is
tracked to solutions at ever increasing resolution). This
approach is motivated by physical smoothness models, deformable
sheets, based on thin elastic membranes and plates. The inherent
smoothness properties of the deformable sheets act against
externally applied, problem specific forces derived from images.
The authors also developed the necessary relations for
quantitative control of scale based parameters so that the scale
space tracking process can be completely automated. Finally, they
present solutions to different problems in computational vision
using the framework applied to real images
Thesaurus computer vision; computerised picture processing
Other Terms adaptive scale space tracking; computational vision; coarse
resolution; physical smoothness models; deformable sheets;
thin elastic membranes; plates; problem specific forces;
necessary relations; quantitative control; scale based
parameters
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4111527
AbstractNos. B9204-6140C-180; C9204-1250-198
ISBN or SBN 0 8186 2057 9
References 12
U.S. Copyright Clearance Center Code
CH2934-8/90/0000-0210$01.00
Country Pub. USA
date 1182
------------------------------------------------------------
Author Deriche, R.; Giraudon, G.;
INRIA Sophia-Antipolis, Valbonne, France
Title Accurate corner detection: an analytical study
Source Proceedings. Third International Conference on Computer Vision
(Cat. No.90CH2934-8); Part: Osaka, Japan; Part: 4-7 Dec. 1990;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xv+759;
1990; pp. 66-70
Abstract Consideration is given to a corner model, and its behavior in the
scale-space is studied. The authors derive results that clarify
the behavior of some well known approaches used to detect corners.
In particular, they show that some of the approaches are
inadequate for an exact localization of the corner. A novel
approach is then proposed in order to correct the displacement
effect and detect exactly the corner position. Some promising
experimental results obtained on real data are shown
Thesaurus computer vision; pattern recognition
Other Terms accurate corner detection; computer vision; corner model;
scale-space; localization; displacement effect
ClassCodes B6140C; C1250
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4111506
AbstractNos. B9204-6140C-159; C9204-1250-177
ISBN or SBN 0 8186 2057 9
References 13
U.S. Copyright Clearance Center Code
CH2934-8/90/0000-0066$01.00
Country Pub. USA
date 1182
------------------------------------------------------------
Author Campos, J.C.; Linney, A.D.; Moss, J.P.;
Dept. of Med. Phys., Univ. Coll. London, UK
Title The analysis of facial profiles using scale space techniques
Source IEE Colloquium on 'Machine Storage and Recognition of Faces'
(Digest No.017); Part: London, UK; Part: 24 Jan. 1992;
Sponsored by: IEE;
London, UK;
IEE;
54;
1992; pp. 10/1-3
Abstract Facial description has always been an interesting and intensive
topic of research, receiving considerable attention over the past
few years in areas such as psychology, bioestereometry, pattern
recognition, forensic science, orthodontics and computer vision.
Many quantifying techniques and methods of analysis have been
proposed. The method developed by the authors has the aim of
producing an objective way of identifying landmarks on the human
profile leading to a useful segmentation and quantitative
description of the contours and features of the face. The main
purpose is that of assessing changes in the profile due to
surgery or growth, but it could also be used on recognition. The
method uses Scale Space techniques, extensively explored in the
fields of digital image and signal processing. They make use of
filtering the signal across a continuum of scales using Gaussian
filters and then tracking the extremal points and their
derivatives as they move with scale changes, yielding a useful
general purpose qualitative description
Thesaurus computerised pattern recognition; computerised picture processing
; medical computing
Other Terms digital image processing; facial features; facial profiles;
human profile; segmentation; quantitative description; Scale
Space techniques; Gaussian filters; qualitative description
ClassCodes C5260B; C7330
Article Type Applications; Practical
Language English
RecordType Conference
ControlNo. 4107289
AbstractNos. C9204-5260B-117
References 0
Country Pub. UK
date 1197
Title IEE Colloquium on 'Machine Storage and Recognition of Faces'
(Digest No.017)
Source Part: London, UK; Part: 24 Jan. 1992;
Sponsored by: IEE;
London, UK;
IEE;
54;
1992
Abstract The following topics were dealt with: an architecture for face
classification; coding facial images for database retrieval; face
recognition algorithm using vector quantization; connectionist
model of familiar face recognition; computer-generated cartoons;
recognising face features and faces; an extended feature set for
automatic face recognition; shape-based description of the facial
surface; analysis of facial profiles using scale space techniques;
and a technique for generation of facial surface models as aid in
orthodontic treatment and orthognathic research
Thesaurus computerised pattern recognition; computerised picture processing
Other Terms face classification; facial images; database retrieval; face
recognition; connectionist model; face features; facial surface
; facial profiles; orthodontic treatment
ClassCodes C5260B
Article Type Practical
Language English
RecordType Conference
ControlNo. 4107280
AbstractNos. C9204-5260B-111
Country Pub. UK
date 1197
------------------------------------------------------------
Author Lindeberg, T.; Eklundh, J.-O.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title Scale-space primal sketch: construction and experiments
Source Image and Vision Computing;
Image Vis. Comput. (UK);
vol.10, no.1;
Jan.-Feb. 1992; pp. 3-18
Abstract Presents a multi-scale representation of grey-level shape, called
the scale-space primal sketch, that makes explicit features in
scale-space as well as the relations between features at
different levels of scale. The representation gives a qualitative
description of the image structure that allows for extraction of
significant image structure-stable scales and regions of interest-
in a solely bottom-up data-driven manner. Hence, it can be seen
as preceding further processing, which can then be properly tuned.
Experiments on real imagery demonstrate that the proposed theory
gives intuitively reasonable results
Thesaurus picture processing
Other Terms scale detection; segmentation; multi-scale representation;
grey-level shape; scale-space primal sketch; real imagery
ClassCodes C1250; C5260B
Article Type Theoretical / Mathematical
Coden IVCODK
Language English
RecordType Journal
ControlNo. 4098695
AbstractNos. C9204-1250-084
ISSN 02628856
References 33
Country Pub. UK
date 1197
------------------------------------------------------------
Author Hong Jeong; Chang-Ik Kim; Woon-Tack Woo;
Pohang Inst. of Sci. & Technol., South Korea
Title Determining optimal scales for edge detection using regularization
Source Proceedings. 1991 IEEE International Conference on Robotics and
Automation (Cat. No.91CH2969-4); Part: Sacramento, CA, USA; Part:
9-11 April 1991;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
3 vol. xxxix+2843;
1991; pp. 1596-601 vol.2
Abstract A regularization method for determining the scales of an edge
detector adaptively for each part of the image is proposed. The
optimal-filter concept of T. Poggio et al. (1984) and the scale
space concept of A. Witkin (1983) are extended to an adaptive
scale parameter. An energy function defined over continuous scale
space is first introduced. Natural constraints for edge detection
are incorporated into the energy function. To obtain a set of
optimal scales which can minimize the energy function, a parallel
relaxation algorithm is introduced. Experiments for synthetic and
natural scenes show the advantages of the new algorithm over the
edge detectors by B. Marr and E. Hildreth (1980) or J.F. Canny
(1986)
Thesaurus filtering and prediction theory; optimisation; pattern
recognition; picture processing; relaxation theory
Other Terms picture processing; pattern recognition; optimal scales; edge
detection; regularization method; optimal-filter concept;
scale space concept; adaptive scale parameter; energy function;
parallel relaxation algorithm
ClassCodes B6140C; B0260; C1250; C1260; C1180
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 4097121
AbstractNos. B9204-6140C-038; C9204-1250-056
ISBN or SBN 0 8186 2163 X
References 11
U.S. Copyright Clearance Center Code
CH2969-4/91/0000-1596$01.00
Country Pub. USA
date 1187
------------------------------------------------------------
Author Nichani, S.; Ranganathan, N.;
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL,
USA
Title SAP: design of a systolic array processor for computation in
vision
Source Proceedings. 1990 IEEE International Conference on Computer
Design: VLSI in Computers and Processors (Cat. No.90CH2909-0); Par
t: Cambridge, MA, USA; Part: 17-19 Sept. 1990;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xx+477;
1990; pp. 315-18
Abstract The design and implementation of SAP chip, a systolic array
processor for computations in vision, is described. The chip can
be used to implement the Gaussian filter, the Laplacian of the
Gaussian filter, and scale space generation. The architecture is
based on an algorithm that can provide speeds an order of
magnitude higher than the speeds of other systems previously
proposed. The algorithm utilises the three properties of Gaussian:
symmetry, separability, and scaling. The algorithm and the
architecture exploit a high degree of pipelining and parallelism
in order to obtain high speed, efficiency, and throughput. The
architecture is adaptable for masks of any size, and the weights
are not restricted to powers of two. The processor was designed
using CMOS technology, fabricated, and tested. The chip is fully
functional and operates at a rate of 10 MHz
Thesaurus CMOS integrated circuits; computer vision; digital signal
processing chips; systolic arrays
Other Terms vision computation; SAP; systolic array processor; design;
implementation; vision; Gaussian filter; Laplacian; scale
space generation; symmetry; separability; scaling; pipelining;
parallelism; CMOS technology; 10 MHz
ClassCodes B1265F; B6140; C5260B
Article Type Practical
Numerical frequency 1.0E+07 Hz
Language English
RecordType Conference
ControlNo. 4097044
AbstractNos. B9204-1265F-029; C9204-5260B-017
ISBN or SBN 0 8186 2079 X
References 14
U.S. Copyright Clearance Center Code
CH2909-0/90/0000-0315$01.00
Country Pub. USA
date 1179
------------------------------------------------------------
Author Liu, Z.-Q.; Rangayyan, R.M.; Frank, C.B.;
Calgary Univ., Alta., Canada
Title Directional analysis of images in scale space
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.13, no.11;
Nov. 1991; pp. 1185-92
Abstract The authors propose a computational technique for the directional
analysis of piecewise linear patterns in images based on the
notion of zero crossings in gradient images. A given image is
preprocessed by a sequence of filters that are second derivatives
of 2-D Gaussian functions with different scales. This gives a set
of zero-crossing maps (the scale space) from which a stability
map is generated. Significant linear patterns are detected from
measurements on the stability map. Information regarding
orientation of the linear patterns in the image and the area
covered by the patterns in specific directions is then computed.
The performance of the method is illustrated through applications
to a simple test image made up of straight bar patterns as well
as to scanning electron microscope images of collagen fibrils in
rabbit ligaments. The method has significant applications in
quantitative analysis of ligament healing and in comparison of
treatment methods for ligament injuries
Thesaurus biology computing; computer vision; filtering and prediction
theory
Other Terms scale space images; directional analysis; piecewise linear
patterns; zero crossings; gradient images; 2-D Gaussian
functions; stability map; orientation; scanning electron
microscope images; collagen fibrils; rabbit ligaments;
ligament healing; treatment methods; ligament injuries
ClassCodes B6140C; C1250; C7330; C1260; C5260B
Article Type Bibliography/Literature Suvery; Practical; Theoretical /
Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 4093258
AbstractNos. B9204-6140C-019; C9204-1250-025
ISSN 01628828
References 51
U.S. Copyright Clearance Center Code
0162-8828/91/1100-1185$01.00
Country Pub. USA
date 1194
------------------------------------------------------------
Author Li-Dong Cai;
Dept. of Artificial Intelligence, Edinburgh Univ., UK
Title Spline smoothing: a special case of diffusion smoothing
Source Fifth Alvey Vision Conference AVC89. Proceedings of the Fifth
Alvey Vision Conference; Part: Reading, UK; Part: 25-28 Sept.
1989;
Sheffield, UK;
Univ. Sheffield;
vi+312;
1989; pp. 273-6
Abstract Diffusion smoothing (DS) implements the smoothing by directly
solving a boundary value problem of the diffusion equation delta
u/ delta t=b Del /sup 2/u with explicit or implicit numerical
schemes, it provides a uniform theoretical base for some other
smoothing methods. It has shown that Gaussian smoothing (GS) is
equivalent to the initial value problem of DS, and repeated
averaging (RA) is a special case of the explicit DS. This paper
further proves that spline smoothing (SS) is a special case of
the explicit DS with a 'convex corner cling' boundary condition.
This result coincides with Poggio's conclusion. However, (1984)
the author's proof starts from the diffusion smoothing theory
instead of regularisation theory and is given in the mask form;
thus it is simpler and more straightforward. Moreover, it makes
it possible to explicit the scale-space behaviour of spline
smoothing
Thesaurus boundary-value problems; computer vision; initial value problems
; partial differential equations; splines (mathematics)
Other Terms computer vision; diffusion smoothing; boundary value problem;
diffusion equation; numerical schemes; Gaussian smoothing;
initial value problem; repeated averaging; spline smoothing;
convex corner cling; mask form; scale-space behaviour
ClassCodes C4130; C4170; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4081621
AbstractNos. C9203-4130-012
References 9
Country Pub. UK
date 1166
------------------------------------------------------------
Author Mussigmann, U.;
Fraunhofer Inst. for Manuf., Eng. & Autom., Stuttgart, Germany
Title Homogeneous fractals and their application in texture analysis
Source Fractals in the Fundamental and Applied Sciences. Proceedings of
the First IFIP Conference; Part: Lisbon, Portugal; Part: 6-8
June 1990;
Sponsored by: IFIP;
Amsterdam, Netherlands;
North-Holland;
ix+461;
1991; pp. 269-83
Editor Peitgen, H.-O.; Henriques, J.M.; Penedo, L.F.
Abstract The theory of multi-fractals can be used for a complete physical
characterization of a fractal set which is inhomogeneous in some
sense. The aim of this paper is to prove some basic properties of
multi-fractal sets which is done by introducing the local
Hausdorff dimension and the local Minkowski dimension. With these
definitions of local fractal dimensions one is able to calculate
a partition of a fractal set into subsets which are homogeneous
with respect to the fractal dimension. For the numerical
computation of the fractal dimension the author uses the so-
called scale space filtering which has been used in image
analysis to describe a discrete signal by its extrema
Thesaurus filtering and prediction theory; fractals
Other Terms texture analysis; multi-fractals; fractal set; local Hausdorff
dimension; local Minkowski dimension; local fractal dimensions;
scale space filtering
ClassCodes C1160; C1260; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 4077269
AbstractNos. C9203-1160-015
ISBN or SBN 0 444 88757 1
References 16
Country Pub. Netherlands
date 1176
------------------------------------------------------------
Author Yi Lu; Vogt, R.C.;
Symbolic Process. Dept., Environ. Res. Inst. of Michigan, Ann
Arbor, MI, USA
Title Multiscale analysis based on mathematical morphology
Source Image Algebra and Morphological Image Processing II; Part: San
Diego, CA, USA; Part: 23-24 July 1991;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1568;
1991; pp. 14-25
Abstract The behaviors of objects described by the morphological scale
space provide strong knowledge for multiscale analysis. The
authors address the two fundamental problems in multiscale
analysis: (1) how to select proper scale parameters for various
applications, and (2) how to integrate the information filtered
at multiscales. They propose two algorithms, Binary Morphological
Multiscale Analysis and Gray scale Morphological Multiscale
Analysis, for extracting desired regions from binary and gray
images
Thesaurus computer vision; filtering and prediction theory
Other Terms binary images; gray scale images; computer vision;
mathematical morphology; morphological scale space; multiscale
analysis; scale parameters
ClassCodes B6140C; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 4046843
AbstractNos. B9201-6140C-145; C9201-5260B-088
ISSN 0277786X
References 11
U.S. Copyright Clearance Center Code
0-8194-0696-1/91/$4.00
Country Pub. USA
date 1208
------------------------------------------------------------
Author Morita, S.; Kawashima, T.; Aoki, Y.;
Fac. of Eng., Hokkaido Univ., Sapporo, Japan
Title Pattern matching of 2-D shape using hierarchical descriptions
Source Systems and Computers in Japan;
Syst. Comput. Jpn. (USA);
vol.22, no.10;
1991; pp. 40-9
Abstract The paper introduces a system for hierarchical description of two-
dimensional shapes on the basis of scale space analysis. The
authors propose a group of simple primitives for describing
curved line segments; they are suitable for hierarchical analysis.
To realize effective matching, nineteen rules are necessary and
sufficient to derive a tree. The tree derived from the analysis
yields the hierarchical structure of a shape and enables
efficient matching of objects in a top-down manner. An algorithm
to create a compact database from trees is also shown. The
sophisticated database is shown to be useful for recognizing
objects by their category. Several examples showed that matching
for skewed or occluded shapes can be done by searching for a
subtree in the database
Thesaurus pattern recognition
Other Terms skewed shapes; contour recognition; hierarchical descriptions;
two-dimensional shapes; scale space analysis; curved line
segments; hierarchical analysis; effective matching;
hierarchical structure; occluded shapes
ClassCodes C1250; C5260B
Article Type Theoretical / Mathematical; Experimental
Coden SCJAEP
Language English
RecordType Journal
ControlNo. 4042465
AbstractNos. C9201-1250-099
ISSN 08821666
References 15
U.S. Copyright Clearance Center Code
0882-1666/91/0010-0040$7.50/0
Country Pub. USA
date 1184
------------------------------------------------------------
Author Jepson, A.D.; Fleet, D.J.;
Dept. of Comput. Sci., Toronto Univ., Ont., Canada
Title Phase singularities in scale-space
Source Image and Vision Computing;
Image Vis. Comput. (UK);
vol.9, no.5;
Oct. 1991; pp. 338-43
Abstract The paper concerns the use of phase information from band-pass
signals for the measurement of binocular disparity, optic flow
and image orientation. Towards this end, one of the important
properties of band-pass phase information is its stability with
respect to small geometric deformations and contrast changes.
However, in particular regions phase can also be very unstable
due to the occurrence of phase singularities. The authors discuss
the existence of phase singularities, and their relation to the
neighbourhoods where phase is unreliable. Moreover, they present
a simple method for detecting these regions of instability
Thesaurus band-pass filters; computerised picture processing; filtering
and prediction theory
Other Terms scale-space; band-pass signals; binocular disparity; optic flow
; image orientation; band-pass phase information; stability;
geometric deformations; contrast changes; phase singularities;
neighbourhoods
ClassCodes B6140C; C5260B
Article Type Experimental
Coden IVCODK
Language English
RecordType Journal
ControlNo. 4033532
AbstractNos. B9201-6140C-051; C9201-5260B-025
ISSN 02628856
References 21
U.S. Copyright Clearance Center Code
0262-8856/91/005338-06$3.00
Country Pub. UK
date 1193
------------------------------------------------------------
Author Lindeberg, T.; Eklundh, J.O.;
Comput. Vision & Active Perception Lab., R. Inst. of Technol.,
Stockholm, Sweden
Title On the computation of a scale-space primal sketch
Source Journal of Visual Communication and Image Representation;
J. Vis. Commun. Image Represent. (USA);
vol.2, no.1;
March 1991; pp. 55-78
Abstract Scale-space is based on a precise mathematical definition of
causality, and the behavior of structure as scale changes can be
analytically described. However, the information in the scale-
space embedding is only implicit. There is no explicit
representation of features or the relations between features at
different levels of scale. A theory is presented for constructing
such an explicit representation on the basis of formal scale-
space theory. The approach is used for gray-level images, but is
valid for any bounded function, and can therefore be used to
derive properties of, e.g., spatial derivatives. Hence it is
useful for studying representations based on intensity
discontinuities as well. The representation is obtained in a
completely data-driven manner. It gives a description of the
image structure that is rather coarse. However, since significant
scales and regions are actually determined from the data, the
approach can be seen as preceding further processing
Thesaurus computerised picture processing
Other Terms multiscale representation; blob detection algorithm; computation
; scale-space primal sketch; gray-level images; bounded
function; intensity discontinuities; image structure
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical; Experimental
Coden JVCRE7
Language English
RecordType Journal
ControlNo. 4008674
AbstractNos. B91071751; C91067508
ISSN 10473203
References 47
Country Pub. USA
date 1186
------------------------------------------------------------
Author Lindeberg, T.; Eklundh, J.-O.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title Analysis of aerosol images using the scale-space primal sketch
Source Machine Vision and Applications;
Mach. Vis. Appl. (USA);
vol.4, no.3;
Summer 1991; pp. 135-44
Abstract The authors outline a method to analyze aerosol images using the
scale-space representation. The pictures, which are photographs
of an aerosol generated by a fuel injector, contain phenomena
that by a human observer are perceived as periodic or oscillatory
structures. The presence of these structures is not immediately
apparent since the periodicity manifests itself at a coarse level
of scale while the dominating objects in the images are small
dark blobs, that is, fine scale objects. Experimentally, they
illustrate that the scale-space theory provides an objective
method to bring out these events. However, in this form the
method still relies on a subjective observer in order to extract
and verify the existence of the periodic phenomena. Then they
extend the analysis by adding a recently developed image analysis
concept called the 'scale-space primal sketch'. With this tool,
they are able to extract significant structures from a grey-level
image automatically without any strong a priori assumptions about
either the shape or the scale (size) of the primitives.
Experiments demonstrate that the periodic drop clusters they
perceived in the image are detected by the algorithm as
significant image structures. These results provide objective
evidence verifying the existence of oscillatory phenomena
Thesaurus aerosols; computerised pattern recognition; computerised
picture processing; flow measurement; two-phase flow
Other Terms perceptual grouping; blob detection; segmentation; fluid
atomization; cluster analysis; aerosol images; scale-space
primal sketch; scale-space representation; photographs; fuel
injector; periodicity; small dark blobs; fine scale objects;
periodic phenomena; image analysis; grey-level image; periodic
drop clusters; significant image structures; oscillatory
phenomena
ClassCodes A4755K; A8270R; A4780; C5260B; C7490; C1250
Article Type Experimental
Coden MVAPEO
Language English
RecordType Journal
ControlNo. 4007049
AbstractNos. A91142086; C91070865
ISSN 09328092
References 18
Country Pub. USA
date 1184
------------------------------------------------------------
Author Wada, T.; Yi He Gu; Sato, M.;
Res. Lab. of Precision Machinery & Electro., Tokyo Inst. of
Technol., Yokohama, Japan
Title Scale-space filtering for periodic waveforms
Source Systems and Computers in Japan;
Syst. Comput. Jpn. (USA);
vol.22, no.6;
1991; pp. 45-54
Abstract The paper describes a method to construct scale-space filtering
so that the monotonicity of the zero crossings applies also to
the periodic waveforms. By analyzing the zero crossings of the
waveform, essential differences between ordinary scale-space
filtering and periodic scale-space filtering are indicated. An
example is presented for the structural analysis of the speech
waveform, and the difference between the hierarchical structures
derived by those scale-space filters is discussed
Thesaurus filtering and prediction theory; speech analysis and processing
Other Terms Gaussian filter; periodic waveforms; scale-space filtering;
monotonicity; zero crossings; structural analysis; speech
waveform; hierarchical structures
ClassCodes B6130; C5260
Article Type Theoretical / Mathematical
Coden SCJAEP
Language English
RecordType Journal
ControlNo. 4006320
AbstractNos. B91071521; C91070755
ISSN 08821666
References 8
U.S. Copyright Clearance Center Code
0882-1666/91/0006-0045$7.50/0
Country Pub. USA
date 1184
------------------------------------------------------------
Author Freeman, M.O.; Saleh, B.E.A.;
Dept. of Electr. & Comput. Eng., Colorado Univ., Boulder, CO, USA
Title Centroid scale-space maps
Source Journal of the Optical Society of America A (Optics and Image
Science);
J. Opt. Soc. Am. A, Opt. Image Sci. (USA);
vol.8, no.9;
Sept. 1991; pp. 1474-87
Abstract An image representation based on mapping image centroids as a
function of spatial and scale variables is introduced. This new
representation has the advantage that the contours within this
scale-space coordinate system consist primarily of curves (i.e.
one-dimensional forms) even when the input function is an image
with two (or more) spatial coordinates. This is contrasted with
the more well-known scale-space approaches based on tracking edge
locations through scale when the scale-space contours become
curved surfaces for two-dimensional input images. The one-
dimensional form of the centroid scale-space contours simplifies
the process of extracting useful information from the scale-space
maps. Centroid scale-space maps for one- and two-dimensional
input functions are examined, and a preliminary set of properties
relating the inputs to the maps is presented. The author
demonstrates the applications of finding the locations and size
distributions of objects in an image and of determining the
medial-axis transform of an image
Thesaurus picture processing
Other Terms centroid scale space maps; image representation; image centroids
; scale variables; scale-space coordinate system; curves; one-
dimensional forms; spatial coordinates; centroid scale-space
contours; two-dimensional input functions; locations; size
distributions; objects; medial-axis transform
ClassCodes A4230V
Article Type Theoretical / Mathematical; Experimental
Coden JOAOD6
Language English
RecordType Journal
ControlNo. 4003735
AbstractNos. A91141365
ISSN 07403232
References 17
U.S. Copyright Clearance Center Code
0740-3232/91/091474-14$05.00
Country Pub. USA
date 1192
------------------------------------------------------------
Author ter Haar Romeny, B.M.; Florack, L.M.J.; Koenderink, J.J.;
Viergever, M.A.;
Utrecht Univ. Hospital, Netherlands
Title Scale space: its natural operators and differential invariants
Source Information Processing in Medical Imaging. 12th International
Conference, IPMI '91 Proceedings; Part: Wye, UK; Part: 7-12
July 1991;
Berlin, Germany;
Springer-Verlag;
xi+512;
1991; pp. 239-55
Editor Colchester, A.C.F.; Hawkes, D.J.
Abstract The authors discuss the fundamental concept of scaling as well as
some natural constraints of a front-end visual system and show
that a complete hierarchical set of scaled differential operators
follows from these considerations. The lowest order kernel is the
isotropic Gaussian. The higher order kernels are the scaled
Gaussian directional derivatives, which form the natural, scaled
differential operators. With this set they can study local image
geometry to any desired order. To this end they introduce the
concept of a local jet of order N, J/sup N/(L(P)), also called N-
jet (Poston and Steward 1978), defined as the equivalence class
of functions L which share the same N-truncated Taylor expansion
at a given point P
Thesaurus invariance; picture processing
Other Terms scaling; front-end visual system; scaled differential operators;
lowest order kernel; isotropic Gaussian; scaled Gaussian
directional derivatives; local image geometry; local jet; N-jet
; equivalence class; N-truncated Taylor expansion
ClassCodes B6140C; C1250; C5260B
Language English
RecordType Conference
ControlNo. 4000432
AbstractNos. B91071828; C91062245
ISBN or SBN 3 540 54246 9
References 29
Country Pub. Germany
date 1190
------------------------------------------------------------
Author Amirfathi, M.M.; Morris, S.; O'Rorke, P.; Bond, W.E.; St. Clair,
D.C.;
Douglas Aircraft Co., Long Beach, CA, USA
Title Pattern recognition for nondestructive evaluation
Source 1991 IEEE Aerospace Applications Conference Digest (Cat. No.
91TH0361-6); Part: Crested Butte, CO, USA; Part: 3-8 Feb. 1991;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
242;
1991; pp. 6/1-11
Abstract The issues involved in automating nondestructive evaluation (NDE)
techniques are outlined. Attention is given to research focused
on the application of machine learning techniques to the
construction and maintenance of knowledge-based systems which are
capable of evaluating the readings from nondestructive tests that
have been performed on aircraft components. Preliminary results
obtained from this research are described. In particular, the
authors discuss the application of a symbolic machine learning
algorithm, ID3, to the NDE problem. ID3 has been used by Douglas
Aircraft to classify defects in sets of standard NDE reference
blocks. Based on the preliminary results, a need for an improved
method of distinguishing features in the test waveforms is
identified. The authors also outline a feature extraction
approach from pattern recognition, called scale-space filtering,
which can be used to preprocess data for input into a
classification algorithm such as ID3
Thesaurus automatic testing; computerised pattern recognition; knowledge
based systems; learning systems; mechanical engineering
computing; nondestructive testing
Other Terms data preprocessing; A-scan; composite materials; artificial
intelligence; NDT; nondestructive evaluation; knowledge-based
systems; nondestructive tests; aircraft components; symbolic
machine learning algorithm; Douglas Aircraft; test waveforms;
feature extraction; pattern recognition; scale-space filtering;
classification algorithm
ClassCodes B0590; B7210B; B7620; C7410H; C5260B; C6170; C7440
Article Type Practical
Language English
RecordType Conference
ControlNo. 4000198
AbstractNos. B91068015; C91066202
ISBN or SBN 0 87942 686 1
References 11
U.S. Copyright Clearance Center Code
TH0361-6/91/0000-0001$01.00
Country Pub. USA
date 1185
------------------------------------------------------------
Author Saint-Marc, P.; Chen, J.-S.; Medioni, G.;
Inst. for Robotics & Intelligent Syst., Univ. of Southern
California, Los Angeles, CA, USA
Title Adaptive smoothing: a general tool for early vision
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.13, no.6;
June 1991; pp. 514-29
Abstract A method to smooth a signal while preserving discontinuities is
presented. This is achieved by repeatedly convolving the signal
with a very small averaging mask weighted by a measure of the
signal continuity at each point. Edge detection can be performed
after a few iterations, and features extracted from the smoothed
signal are correctly localized (hence, no tracking is needed).
This last property allows the derivation of a scale-space
representation of a signal using the adaptive smoothing parameter
k as the scale dimension. The relation of this process to
anisotropic diffusion is shown. A scheme to preserve higher-order
discontinuities and results on range images is proposed.
Different implementations of adaptive smoothing are presented,
first on a serial machine, for which a multigrid algorithm is
proposed to speed up the smoothing effect, then on a single
instruction multiple data (SIMD) parallel machine such as the
Connection Machine. Various applications of adaptive smoothing
such as edge detection, range image feature extraction, corner
detection, and stereo matching are discussed
Thesaurus adaptive filters; computer vision; computerised pattern
recognition; computerised picture processing; filtering and
prediction theory
Other Terms machine vision; computer vision; pattern recognition; adaptive
filtering; scale-space representation; adaptive smoothing;
anisotropic diffusion; SIMD; parallel machine; Connection
Machine; edge detection; feature extraction; corner detection;
stereo matching
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3991725
AbstractNos. B91071716; C91062173
ISSN 01628828
References 39
U.S. Copyright Clearance Center Code
0162-8828/91/0600-0514$01.00
Country Pub. USA
date 1189
------------------------------------------------------------
Author Ueda, N.; Suzuki, S.;
Human Interface Labs., NTT, Yokosuka, Japan
Title A matching algorithm of deformed planar curves using multiscale
convex/concave structures
Source Systems and Computers in Japan;
Syst. Comput. Jpn. (USA);
vol.22, no.5;
1991; pp. 94-104
Abstract The paper proposes a new multiscale segment matching method which
is applicable to heavily deformed planar shapes. First,
multiscale representations are obtained using curvature scale
space filtering. Then inflection point correspondence is
developed between consecutive smoothed shapes. The representation
in this paper, unlike the well-known curvature scale space image
description, ensures that it always satisfies the consistency of
hierarchical segment replacement. Moreover, it requires less
processing time and memory allocation. Finally, optimum scale
segments are matched by a new multiscale segment matching method
proposed herein. In this method, the matching problem is
formulated as a minimization problem of the total amount of
segment dissimilarity. The minimization problem is solved
effectively using dynamic programming. The proposed matching
method makes it possible to obtain intuitively relevant
correspondences even if the shapes have some local heavy
deformation
Thesaurus computerised pattern recognition; filtering and prediction theory
Other Terms matching algorithm; deformed planar curves; multiscale
convex/concave structures; multiscale segment matching method;
heavily deformed planar shapes; multiscale representations;
curvature scale space filtering; inflection point correspondence;
smoothed shapes; hierarchical segment replacement; processing
time; memory allocation; minimization problem; segment
dissimilarity; dynamic programming; intuitively relevant
correspondences; local heavy deformation
ClassCodes C5260B; C1250; C1260
Article Type Theoretical / Mathematical
Coden SCJAEP
Language English
RecordType Journal
ControlNo. 3982095
AbstractNos. C91064000
ISSN 08821666
References 4
U.S. Copyright Clearance Center Code
0882-1666/91/0005-0094$7.50/0
Country Pub. USA
date 1184
------------------------------------------------------------
Author Liu, Z.-Q.; Rangayyan, R.M.; Frank, C.B.;
Novatel Commun. Ltd., Calgary, Alta., Canada
Title Statistical analysis of collagen alignment in ligaments by scale-
space analysis
Source IEEE Transactions on Biomedical Engineering;
IEEE Trans. Biomed. Eng. (USA);
vol.38, no.6;
June 1991; pp. 580-8
Abstract The authors propose a computational technique for statistical
analysis of collagen alignment in ligament images using the scale-
space approach. In this method, a ligament image is preprocessed
by a sequence of filters which are second derivatives of two-
dimensional Gaussian functions with different scales. This gives
a set of zero-crossing maps (the scale space) from which a
stability map is generated. Significant linear patterns are
captured by analyzing the stability map. The directional
information in terms of orientation distributions of the collagen
fibrils in the image and the area covered by the fibrils in
specific directions is extracted for statistical analysis.
Examples illustrating the performance of this method with
scanning electron microscope images of the collagen fibrils in
healing rabbit medial collateral ligaments are presented
Thesaurus picture processing; proteins; statistical analysis
Other Terms 2D Gaussian functions; image preprocessing; filters sequence;
collagen alignment; scale-space analysis; computational
technique; zero-crossing maps; linear patterns; stability map;
collagen fibrils; scanning electron microscope images; healing
rabbit medial collateral ligaments
ClassCodes A8710
Article Type Theoretical / Mathematical
Coden IEBEAX
Language English
RecordType Journal
ControlNo. 3971104
AbstractNos. A91123964
ISSN 00189294
References 32
U.S. Copyright Clearance Center Code
0018-9294/91/0600-0580$01.00
Country Pub. USA
date 1189
------------------------------------------------------------
Author Cumani, A.; Grattoni, P.; Guiducci, A.;
Istituto Elettrotecnico Nazionale Galileo Ferraris, Torino, Italy
Title An edge-based description of color images
Source CVGIP: Graphical Models and Image Processing;
CVGIP, Graph. Models Image Process. (USA);
vol.53, no.4;
July 1991; pp. 313-23
Abstract This paper presents a method of describing multispectral images,
for computer vision applications, in terms of contour elements.
Contours are detected, at different scales of resolution, as the
zero crossings of a second-order differential operator that
represents an extension of the second directional derivative to
the multispectral case. A fine-to-coarse analysis of contour
behavior in scale space is then used to compute the attributes
needed for the description of the image. Subsequent contour
segmentation, based on both geometric and photometric features,
allows for a further increase in description compactness without
significant losses of information. In order to assess the
faithfulness of the description, it is shown that an approximate
reconstruction of the original image can be obtained from the
coded contours. The method has been tested on several real-world
colour images. Two examples, in which images are described and
reconstructed at different degrees of compactness, allowing for
an objective and subjective evaluation of the performance of the
method, are presented
Thesaurus computer vision; computerised picture processing
Other Terms edge-based description; color images; multispectral images;
computer vision; contour elements; zero crossings; second-
order differential operator; fine-to-coarse analysis; coded
contours
ClassCodes C1250; C5260B
Article Type Practical
Coden CGMPE5
Language English
RecordType Journal
ControlNo. 3964020
AbstractNos. C91055741
ISSN 10499652
References 22
Country Pub. USA
date 1190
------------------------------------------------------------
Author Wada, T.; Sato, M.;
Res. Lab. of Precision Machinery & Electron., Tokyo Inst. of
Technol., Japan
Title Scale-space tree and its hierarchy
Source Proceedings. 10th International Conference on Pattern Recognition
(Cat. No.90CH2898-5); Part: Atlantic City, NJ, USA; Part: 16-21
June 1990;
Sponsored by: Int. Assoc. Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
2 vol. (xxxi+xxv+1676);
1990; pp. 103-8 vol.2
Abstract Scale-space filtering is a multiresolutional filtering method
which expands a waveform to the set of waveforms in multiscale
measurement. The intervals bounded by zero-crossings of expanded
waveforms have a hierarchical structure, which can be represented
by an interval tree. Another hierarchical description of the
waveform, scale-space tree, is introduced as a natural
description of the hierarchy. The difference hierarchy between
the interval tree and the scale-space tree is discussed
Thesaurus filtering and prediction theory; picture processing
Other Terms scale-space filtering; multiresolutional filtering; waveforms;
multiscale measurement; zero-crossings; hierarchical structure;
interval tree; scale-space tree
ClassCodes B6140C; C1260; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3957030
AbstractNos. B91058384; C91051183
ISBN or SBN 0 8186 2062 5
References 8
U.S. Copyright Clearance Center Code
CH2898-5/90/0000-0103$01.00
Country Pub. USA
date 1176
------------------------------------------------------------
Author Woo Young Choi; Jong Soo Choi; San Uk Lee; Rae Hong Park;
Dept. of Electr. Eng., Sogang Univ., Seoul, South Korea
Title Stereo matching using finger print on the scale space
Source Journal of the Korean Institute of Telematics and Electronics;
J. Korean Inst. Telemat. Electron. (South Korea);
vol.28B, no.2;
Feb. 1991; pp. 53-60
Abstract Proposes a stereo correspondence matching algorithm using the
finger print (characteristic pattern) of zero-crossing points on
the scale-space as the robust feature. In the authors' approach
they extract the finger print corresponding to the authentic zero-
crossing edge along the scale value due to the maximum principle.
Since most of the objects cannot be matched by only their local
feature values, they used the relaxation matching method using
not only the feature values but also the available contextual
information. In simulation, they applied the proposed algorithm
to synthetic and natural images and obtained good matching results
Thesaurus computerised picture processing
Other Terms pattern of zero-crossing points; stereo image matching;
synthetic images; stereo correspondence matching algorithm;
scale-space; zero-crossing edge; relaxation matching method;
contextual information; natural images; matching results
ClassCodes B6140C; C5260B; C7410F
Article Type Theoretical / Mathematical; Experimental
Coden CKNOEZ
Language English
RecordType Journal
ControlNo. 3953479
AbstractNos. B91058192; C91052608
References 12
Country Pub. South Korea
date 1185
------------------------------------------------------------
Author Raman, S.V.; Sarkar, S.; Boyer, K.L.;
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Title Tissue boundary refinement in magnetic resonance images using
contour-based scale space matching
Source IEEE Transactions on Medical Imaging;
IEEE Trans. Med. Imaging (USA);
vol.10, no.2;
June 1991; pp. 109-21
Abstract An algorithm for computationally focusing the tissue boundaries
detected from magnetic resonance images is presented. The
proposed approach is a novel, whole-contour-based technique for
tracing edges selected at a coarse scale into successively finer
scales to recover the needed precision. The tracing algorithm
builds consensus through a fast pixel voting scheme. Also
presented is a rigorous method for determining the appropriate
itinerary when traversing scale space, beginning from the premise
of a maximum pixel migration per unit change in scale parameter.
This leads to an efficient method of processing images so as to
maximize accuracy and minimize noise. Although the LoG (Laplacian
of Gaussian) is used for many of the experiments, results using a
novel edge detector which is mathematically superior to and
faster to compute than the LoG and for which fewer steps are
required to traverse the same effective span in scale space are
presented. Experimental results on real data are presented, and
other potential applications are discussed
Thesaurus biomedical NMR; picture processing
Other Terms tissue boundary refinement; edge tracing; fine scale; magnetic
resonance images; contour-based scale space matching; algorithm;
whole-contour-based technique; coarse scale; fast pixel
voting scheme; itinerary; scale parameter; Laplacian of
Gaussian
ClassCodes A8760G; A8770E; A8740
Article Type Theoretical / Mathematical
Coden ITMID4
Language English
RecordType Journal
ControlNo. 3947079
AbstractNos. A91112501
ISSN 02780062
References 23
U.S. Copyright Clearance Center Code
0278-0062/91/0600-0109$01.00
Country Pub. USA
date 1189
------------------------------------------------------------
Author Wilson, R.; Clippingdale, S.; Bhalerao, A.H.;
Dept. of Comput. Sci., Warwick Univ., Coventry, UK
Title Robust estimation of local orientations in images using a
multiresolution approach
Source Visual Communications and Image Processing '90; Part: Lausanne,
Switzerland; Part: 1-4 Oct. 1990;
Sponsored by: SPIE; Swiss Federal Inst. Technol;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1360, pt.3;
1990; pp. 1393-1403
Abstract The problem of estimating feature orientation from noisy image
data is addressed. It is shown that by appropriate choice of
representation of orientation, it is possible to employ simple
linear smoothing methods to reduce estimation noise. A
combination of scale-space recursive filtering and iterative
estimation gives significant improvements in estimated
orientations at low computational cost. Applications to
enhancement and are presented
Thesaurus estimation theory; filtering and prediction theory; iterative
methods; picture processing
Other Terms multiresolution approach; feature orientation; noisy image data;
linear smoothing; scale-space recursive filtering; iterative
estimation; computational cost; enhancement
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3946751
AbstractNos. B91058279; C91050880
ISSN 0277786X
References 18
Country Pub. USA
date 1180
------------------------------------------------------------
Author Ren, Z.; Ameling, W.; Jensch, P.;
Rogowski-Inst. fur Elektrotech., Tech. Hochschule Aachen, Germany
Title An attributed tree data structure for representing the
descriptions of object contours in images
Source Visual Communications and Image Processing '90; Part: Lausanne,
Switzerland; Part: 1-4 Oct. 1990;
Sponsored by: SPIE; Swiss Federal Inst. Technol;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1360, pt.2;
1990; pp. 956-69
Abstract The shapes of medical objects, e.g. human bones or skeletons,
conveys information about anatomic structures and pathological
states. The sectional contours of objects observable through
computer tomograms provide descriptive clues for analyzing shapes.
Sectional contours of medical objects are highly curved and
complex and therefore should be described in a higher order
parameter space. These considerations have guided the authors to
examine the scale-space transformation, and to develop methods
for expressing, describing, and extracting structures in the
scale-space images of the contours. This paper introduces a tree-
based data structure for representing descriptions of structures
in the scale-space, and further demonstrates its applications to
shape analysis
Thesaurus computerised tomography; data structures; medical diagnostic
computing; trees (mathematics)
Other Terms descriptions of object contours; medical objects; sectional
contours; computer tomograms; scale-space transformation; tree-
based data structure; shape analysis
ClassCodes A8760J; A8710; B6140C; C7330; C5260B; C6120
Article Type Applications; Practical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3946721
AbstractNos. A91104852; B91058253; C91054342
ISSN 0277786X
References 30
Country Pub. USA
date 1180
------------------------------------------------------------
Author Wilson, R.; Todd, M.; Calway, A.D.;
Dept. of Comput. Sci., Warwick Univ., Coventry, UK
Title Generalized quad-trees: a unified approach to multiresolution
image analysis and coding
Source Visual Communications and Image Processing '90; Part: Lausanne,
Switzerland; Part: 1-4 Oct. 1990;
Sponsored by: SPIE; Swiss Federal Inst. Technol;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1360, pt.1;
1990; pp. 619-26
Abstract This paper is an attempt to bring a number of current ideas in
multiresolution image processing into a single framework. The
unification is achieved by a two-level image model, comprising a
quadtree containing parameters which control the evolution of the
image as a sequence of successive refinements through scale-space.
Examples of the method's application to image coding and analysis
illustrate the principles and show its usefulness
Thesaurus encoding; hierarchical systems; picture processing
Other Terms multiresolution image analysis; image processing; two-level
image model; quadtree; sequence of successive refinements;
image coding
ClassCodes B6140C; B6120B; C1250
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3946707
AbstractNos. B91058239; C91050842
ISSN 0277786X
References 18
Country Pub. USA
date 1180
------------------------------------------------------------
Author Rattarangsi, A.; Chin, R.T.;
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Title Scale-based detection of corners of planar curves
Source Proceedings. 10th International Conference on Pattern Recognition
(Cat. No.90CH2898-5); Part: Atlantic City, NJ, USA; Part: 16-21
June 1990;
Sponsored by: Int. Assoc. Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
2 vol. (xxxi+xxv+1676);
1990; pp. 923-30 vol.1
Abstract A technique for detecting and localizing corners of planar curves
is proposed. The technique is based on Gaussian scale space,
which consists of the maxima of absolute curvature of the
boundary function presented at all scales. The scale space of
isolated simple and double corners is analyzed to investigate the
behavior of scale space due to smoothing and interactions between
two adjacent corners. The scale space is transformed into a tree
which provides simple but concise representation of corners at
multiple scales. A multiple-scale corner detection scheme is
developed using a coarse-to-fine tree parsing technique. The
parsing scheme is based on a stability criterion which states
that the presence of a corner must concur with a curvature
maximum observable at a majority of scales. Experimental results
show that the scale-space corner detector is reliable for objects
with multiple-size features and noisy boundaries and that it
compares favorably with other corner detectors tested
Thesaurus grammars; pattern recognition; picture processing; trees
(mathematics)
Other Terms planar curve corner detection; Gaussian scale space; absolute
curvature; boundary function; scale space; tree parsing;
stability criterion; scale-space corner detector
ClassCodes B6140C; B0250; C1250; C1160; C4210
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3944495
AbstractNos. B91051673; C91051046
ISBN or SBN 0 8186 2062 5
References 20
U.S. Copyright Clearance Center Code
CH2898-5/90/0000-0923$01.00
Country Pub. USA
date 1176
------------------------------------------------------------
Author Wu, Y.; Maitre, H.;
Telecom, Paris, France
Title Registration of a SPOT image and a SAR image using
multiresolution representation of a coastline
Source Proceedings. 10th International Conference on Pattern Recognition
(Cat. No.90CH2898-5); Part: Atlantic City, NJ, USA; Part: 16-21
June 1990;
Sponsored by: Int. Assoc. Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
2 vol. (xxxi+xxv+1676);
1990; pp. 913-17 vol.1
Abstract A novel method is presented for the registration of a SPOT
satellite image against a Seasat synthetic aperture radar (SAR)
image. An edge following technique is proposed. It is adapted to
very noisy images such as SAR images. It is shown that, by the
use of a multiresolution method, a directional graph can be
constructed which gives a clearer definition of the equivalence
between edge following and optimal path search on a graph. A
hypothesis-testing approach, also based on a multiresolution
method, is proposed to solve the registration problem. The
hypotheses are drawn from scale space representations in order to
maintain a low complexity. These hypotheses are then tested by a
chamfer distance map. By the combination of scale space
representation and the chamfer matching method, a very robust and
fast registration results
Thesaurus computerised picture processing; geophysical techniques; graph
theory; oceanographic techniques; remote sensing; remote
sensing by radar
Other Terms remote sensing; computerised picture processing; SPOT image;
SAR image; multiresolution representation; coastline; edge
following technique; directional graph; optimal path search;
scale space representations; chamfer distance map
ClassCodes A9385; A9210; A9190; B7710; B7730; B6140C; B0250; C7340;
C5260B; C1160
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3944493
AbstractNos. A91100025; B91053354; C91054395
ISBN or SBN 0 8186 2062 5
References 21
U.S. Copyright Clearance Center Code
CH2898-5/90/0000-0913$01.00
Country Pub. USA
date 1176
------------------------------------------------------------
Author Ueda, N.; Suzuki, S.;
NTT Corp., Yokosuka, Japan
Title Automatic shape model acquisition using multiscale segment
matching
Source Proceedings. 10th International Conference on Pattern Recognition
(Cat. No.90CH2898-5); Part: Atlantic City, NJ, USA; Part: 16-21
June 1990;
Sponsored by: Int. Assoc. Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
2 vol. (xxxi+xxv+1676);
1990; pp. 897-902 vol.1
Abstract A novel method for acquiring a shape model from shape samples of
the same class is proposed. A critical point is that the method
requires no prior knowledge of the class. Multiscale
representations are first obtained using curvature scale space
filtering to gain inflection point correspondence between
consecutive smoothed shapes. The multiscale samples are then
matched to extract the convex/concave structure common to the
class. The matching is invariant under translation, rotation, and
size change. Finally, generalized samples composing a model are
generated by smoothly connecting the matched convex and concave
segments. Experimental results show that the resulting model is
useful for shape recognition
Thesaurus filtering and prediction theory; pattern recognition; picture
processing
Other Terms multiscale representation; picture processing; pattern
recognition; shape model acquisition; multiscale segment
matching; curvature scale space filtering; convex/concave
structure; shape recognition
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3944490
AbstractNos. B91051670; C91051042
ISBN or SBN 0 8186 2062 5
References 11
U.S. Copyright Clearance Center Code
CH2898-5/90/0000-0897$01.00
Country Pub. USA
date 1176
------------------------------------------------------------
Author Allmen, M.; Dyer, C.R.;
Dept. of Comput. Sci., Wisconsin Univ., Madison, WI, USA
Title Cyclic motion detection using spatiotemporal surfaces and curves
Source Proceedings. 10th International Conference on Pattern Recognition
(Cat. No.90CH2898-5); Part: Atlantic City, NJ, USA; Part: 16-21
June 1990;
Sponsored by: Int. Assoc. Pattern Recognition;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
2 vol. (xxxi+xxv+1676);
1990; pp. 365-70 vol.1
Abstract Cyclic motion is formally defined as repeating curvature values
along a path of motion. A procedure is presented for cyclic
motion detection using spatiotemporal (ST) surfaces and ST curves.
The projected movement of an object generates ST surfaces. ST
curves are detected on the ST surfaces, providing an accurate,
compact, qualitative description of the ST surfaces. Curvature
scale-space of the ST curves is then used to detect intervals of
repeating curvature values. The successful detection of cyclic
motion in two data sets is presented
Thesaurus pattern recognition; visual perception
Other Terms spatiotemporal curves; curvature scale-space; spatiotemporal
surfaces; cyclic motion detection; repeating curvature values
ClassCodes A8732S; B6140C; C1250; C1290L
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3944398
AbstractNos. A91104717; B91051616; C91050975
ISBN or SBN 0 8186 2062 5
References 19
U.S. Copyright Clearance Center Code
CH2898-5/90/0000-0365$01.00
Country Pub. USA
date 1176
------------------------------------------------------------
Author Ueda, N.; Suzuki, S.;
NTT Human Interface Lab., Tokyo, Japan
Title Multiscale convex/concave structure matching -MC matching method
Source NTT R & D;
NTT R & D (Japan);
vol.40, no.3;
1991; pp. 399-406
Abstract Proposes a new multiscale segment matching method that is
applicable to heavily deformed planar shapes. First, multiscale
representations are obtained using curvature scale space
filtering, which requires less processing time and memory
allocation than the well-known curvature scale space image
description. Then, inflection point correspondence is developed
between consecutive smoothed shapes. Finally, optimum scale
segment correspondences are determined from all possible
combinations of the two multiscale representations. The procedure
is performed effectively using dynamic programming. The proposed
matching method makes it possible to obtain intuitively relevant
correspondences even if the shapes have some local heavy
deformation
Thesaurus computerised pattern recognition; dynamic programming
Other Terms multiscale convex structure matching; multiscale concave
structure matching; multiscale segment matching; deformed
planar shapes; curvature scale space filtering; inflection point
; optimum scale segment correspondences; dynamic programming
ClassCodes B6140C; B0260; C5260B; C1180
Article Type Practical
Coden NTTDEC
Language Japanese
RecordType Journal
ControlNo. 3942045
AbstractNos. B91051494; C91052611
ISSN 09152326
References 7
Country Pub. Japan
date 1184
------------------------------------------------------------
Author Zhi-Qiang Liu;
Dept. of Adv. Digital Process., Novatel Commun. Ltd., Calgary,
Alta., Canada
Title Scale space approach to directional analysis of images
Source Applied Optics;
Appl. Opt. (USA);
vol.30, no.11;
10 April 1991; pp. 1369-73
Abstract A new technique for directional analysis of linear patterns in
images is proposed based on the notion of scale space. A given
image is preprocessed by a sequence of filters which are second
derivatives of 2-D Gaussian functions with different scales. This
gives a set of zero crossing maps (the scale space) from which a
stability map is generated. Significant linear patterns are
detected from measurements on the stability map. Information
regarding orientation of the linear patterns in the image and the
area covered by the patterns in specific directions is then
computed. The performance of the method is illustrated through
applications to synthetic patterns and to scanning electron
microscope images of collagen fibrils in rabbit ligaments
Thesaurus biological techniques and instruments; computerised pattern
recognition; computerised picture processing; scanning electron
microscope examination of materials
Other Terms filter sequence; 2D Gaussian function second derivatives;
computer vision; directional analysis; images; linear patterns;
scale space; zero crossing maps; stability map; linear
patterns; synthetic patterns; scanning electron microscope
images; collagen fibrils; rabbit ligaments
ClassCodes A0650D; A4230V; A0780; A8780; A4230S; B6140C; C1250
Article Type New Development; Practical; Theoretical / Mathematical;
Experimental
Coden APOPAI
Language English
RecordType Journal
ControlNo. 3928839
AbstractNos. A91089235; B91051452; C91044927
ISSN 00036935
References 23
U.S. Copyright Clearance Center Code
0003-6935/91/111369-05$05.00/0
Country Pub. USA
date 1187
------------------------------------------------------------
Author Vincken, K.L.; de Graaf, C.N.; Koster, A.S.E.; Viergever, M.A.;
Appelman, F.J.R.; Timmens, G.R.;
Utrecht Univ., Netherlands
Title Multiresolution segmentation of 3D images by the hyperstack
Source Proceedings of the First Conference on Visualization in
Biomedical Computing (Cat. No.90TH0311-1); Part: Atlanta, GA, USA
; Part: 22-25 May 1990;
Sponsored by: IEEE; Georgia Inst. Technol.; NSF; Emory Univ.
School of Med.; et al;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xii+520;
1990; pp. 115-22
Abstract An improvement in the design of the hyperstack, a three-
dimensional image segmentation tool, is described. It is based on
a multiresolution approach which is mathematically supported by
the diffusion equation. The blurring strategy, used to build the
scale space, is outlined, including some difficulties that occur
in view of the transition from 2-D to 3-D. The existing prototype,
a hyperstack grounded on isointensity following, is extended by
two novel ideas: weighted linking and stand-alone parents. The
result of a segmented 3D SPECT image (of a liver) is shown.
Theoretical considerations concerning the addition of feature
information to guide the segmentation process are briefly
mentioned. A flexible way to obtain several output images from
one single hyperstack is outlined and the reduction of the
sampling rate by means of interpolation, which will decrease the
total amount of processing time, is investigated
Thesaurus computerised pattern recognition; computerised picture processing
; data structures; medical computing
Other Terms data structure; 3D images; hyperstack; three-dimensional image
segmentation tool; multiresolution; diffusion equation;
blurring strategy; scale space; isointensity following;
weighted linking; stand-alone parents; segmented 3D SPECT image;
liver; feature information; segmentation; sampling rate;
interpolation; processing time
ClassCodes C5260B; C7330
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3926454
AbstractNos. C91047206
ISBN or SBN 0 8186 2039 0
References 10
U.S. Copyright Clearance Center Code
TH0311-1/90/0000-0115$01.00
Country Pub. USA
date 1175
------------------------------------------------------------
Author Cullip, T.J.; Fredericksen, R.E.; Gauch, J.M.; Pizer, S.M.;
North Carolina Univ., Chapel Hill, NC, USA
Title Algorithms for 2D and 3D image description based on the IAS
Source Proceedings of the First Conference on Visualization in
Biomedical Computing (Cat. No.90TH0311-1); Part: Atlanta, GA, USA
; Part: 22-25 May 1990;
Sponsored by: IEEE; Georgia Inst. Technol.; NSF; Emory Univ.
School of Med.; et al;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
xii+520;
1990; pp. 102-7
Abstract The algorithms used in computing the intensity axis of symmetry
(IAS) for 2D and 3D medical images are described. The basic 2D
algorithms, along with the algorithms needed to incorporate scale
space, are described. A brief discussion of the extensions needed
to work with 3D images is given. The basic approach is to treat
the image as a deformable intensity surface which is contracted
onto the IAS. The primitive regions of the segmentation are
identified by the branches in the resulting tree-like structure.
A hierarchy is produced by following the simplification of the
branching through scale space. For comparison papers see ibid., p.
94-101 and ibid., p.108-14
Thesaurus computerised picture processing; medical computing
Other Terms CT image; chest; MRI image; brain; ridge structures;
branching structures; IAS segmentation; image segmentation; 2D
and 3D image description; IAS; intensity axis of symmetry;
medical images; deformable intensity surface; primitive regions;
segmentation; branching; scale space
ClassCodes C5260B; C7330
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3926452
AbstractNos. C91047204
ISBN or SBN 0 8186 2039 0
References 3
U.S. Copyright Clearance Center Code
TH0311-1/90/0000-0102$01.00
Country Pub. USA
date 1175
------------------------------------------------------------
Author Bengtsson, A.; Eklundh, J.-O.;
Comput. Vision & Active Perception Lab., R. Inst. of Technol.,
Stockholm, Sweden
Title Shape representation by multiscale contour approximation
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.13, no.1;
Jan. 1991; pp. 85-93
Abstract An approach is presented for deriving qualitative descriptions of
contours containing structures at different (unknown) scales. The
descriptions are in terms of straight arcs, curved arcs with sign
of curvature, corners, and points delimiting the arcs: inflexion
points and transitions from straight to curved. Furthermore, the
tangents at these points are derived. The approach is based on
the construction of a hierarchic family of polygons, having the
scale-space property of causality; structure can only disappear
as scale goes from fine to coarse. Using the principle that
structures that are stable over scale represent significant
properties, the features of the descriptive representations are
then derived
Thesaurus computer vision; computerised pattern recognition; computerised
picture processing
Other Terms shape representation; scale stability; multiscale contour
approximation; qualitative descriptions; straight arcs; curved
arcs; corners; points delimiting the arcs; inflexion points;
polygons; scale-space property of causality
ClassCodes C5260; C1250
Article Type Theoretical / Mathematical; Experimental
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3880519
AbstractNos. C91035561
ISSN 01628828
References 27
U.S. Copyright Clearance Center Code
0162-8828/91/0100-0085$01.00
Country Pub. USA
date 1184
------------------------------------------------------------
Author Estola, K.-P.;
Nokia Mobile Phones, Salo, Finland
Title Interpolated Gaussian scale-space filters
Source ICASSP 90. 1990 International Conference on Acoustics, Speech and
Signal Processing (Cat. No.90CH2847-2); Part: Albuquerque, NM,
USA; Part: 3-6 April 1990;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
5 vol. 2970;
1990; pp. 2073-6 vol.4
Abstract Computationally efficient interpolated Gaussian scale-space
filters are introduced. The proposed scale-space filters
incorporate multirate signal-processing methods and are realized
using multistage filter structures. The scale-space filters can
also be used in decimating the data, if desired. The proposed
filtering methods require dramatically less computation than
conventional Gaussian scale-space filtering, especially where the
scale changes with an integer factor. The filters are extremely
efficient when the change in scale is an integer power of an
integer constant
Thesaurus filtering and prediction theory; interpolation; signal
processing
Other Terms interpolated Gaussian scale-space filters; multirate signal-
processing methods; multistage filter structures
ClassCodes B6140; B0290F
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3875736
AbstractNos. B91033196
References 4
U.S. Copyright Clearance Center Code
CH2847-2/90/0000-2073$01.00
Country Pub. USA
date 1174
------------------------------------------------------------
Author Zuerndorfer, B.; Wakefield, G.H.; England, A.W.;
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor,
MI, USA
Title Recovery of fine resolution information in multispectral
processing
Source ICASSP 90. 1990 International Conference on Acoustics, Speech and
Signal Processing (Cat. No.90CH2847-2); Part: Albuquerque, NM,
USA; Part: 3-6 April 1990;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
5 vol. 2970;
1990; pp. 2033-6 vol.4
Abstract Multiple-sensor processing is considered, and a unified method
for representing multiple-sensor data is developed. When
resolution varies between sensors, such a multiple-sensor system
can be viewed as samples of a scale-space signal representation.
It is demonstrated that if the spatial transfer function of the
sensors are Gaussian, then scale-space filtering can be used to
recover small-scale (fine-resolution) information through
extrapolation in scale. As an example of multiple-sensor
processing, multispectral processing of remote sensing, in which
images of surface scenes are simultaneously generated at
different (center) frequencies, is considered. The fingerprints
of extrapolated signals approximate the actual multispectral
fingerprints at small scales and can be used when the
multispectral fingerprints are not available
Thesaurus computerised pattern recognition; computerised picture processing
; filtering and prediction theory; remote sensing
Other Terms fine resolution information recovery; Gaussian spatial transfer
function; surface scene images; scale-space filtering;
multiple-sensor processing; multispectral processing; remote
sensing; extrapolated signals; multispectral fingerprints
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3875726
AbstractNos. B91033569; C91026462
References 11
U.S. Copyright Clearance Center Code
CH2847-2/90/0000-2033$01.00
Country Pub. USA
date 1174
------------------------------------------------------------
Author Cung, H.M.; Cohen, P.; Boulanger, P.;
Dept. of Electr. Eng., Ecole Polytech. de Montreal, Que., Canada
Title Multiscale edge detection and classification in range images
Source Proceedings 1990 IEEE International Conference on Robotics and
Automation (Cat. No.90CH2876-1); Part: Cincinnati, OH, USA; Part:
13-18 May 1990;
Sponsored by: IEEE;
Los Alamitos, CA, USA;
IEEE Comput. Soc. Press;
3 vol. xxxii+2184;
1990; pp. 2038-44 vol.3
Abstract An edge detection and classification scheme for range images
which produces a multiscale representation in terms of well-
localized depth and orientation edges is presented. The
extraction is accomplished by detecting the presence of
significant edges at a coarse scale and then determining their
precise location by tracking them over decreasing scale. An
adaptive multiscale thresholding is applied during this focusing
process ro inhibit the attraction of insignificant details. Once
focused, the edges are classified into the categories of true
edge and diffuse edge by invoking classification rules derived
from a mathematical analysis of edge displacement and branching
over scale-space. Experimental results illustrate the robustness
of the approach in the presence of noise and its performance with
synthetic and real images of varying complexity. Comparisons with
recently published techniques point out the improved performance
of the approach, especially when the images contain substantially
overlapping objects
Thesaurus pattern recognition; picture processing
Other Terms multiscale edge detection; edge classification; localized depth
edges; range images; multiscale representation; orientation
edges; tracking; adaptive multiscale thresholding; edge
displacement; branching; scale-space; noise
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3875316
AbstractNos. B91033543; C91026438
ISBN or SBN 0 8186 9061 5
References 16
U.S. Copyright Clearance Center Code
CH2876-1/90/0000-2038$1.00
Country Pub. USA
date 1175
------------------------------------------------------------
Author de Ridder, H.; Majoor, G.M.M.;
Inst. for Perception Res., Eindhoven, Netherlands
Title Numerical category scaling: an efficient method for assessing
digital image coding impairments
Source Human Vision and Electronic Imaging: Models, Methods and
Applications; Part: Santa Clara, CA, USA; Part: 12-14 Feb. 1990;
Sponsored by: SPIE; SPSE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1249;
1990; pp. 65-77
Abstract A problem in perceptual image quality assessment is the
evaluation of the visible effects of digital image coding on the
perceptual quality of images displayed on video screens. These
effects are anticipated to be too small to be assessed by the
widely employed method of rating on a category scale consisting
of adjectives. A possible solution to this problem is to enhance
the flexibility of category scaling by using numbers instead of
adjectives. Experiments are described in which numerical category
scaling has been used to assess impairment of perceptual image
quality due to quantization errors in scale-space coding. The
results show that direct numerical category scaling is an
efficient method for assessing slight effects like the ones
usually encountered in digitally coded images; direct category
scaling and a scaling procedure in accordance with functional
measurement theory end in the same functional relationship
between impairment and degree of quantization; and unrelated
impairments add up to form the overall impression of impairment
Thesaurus analogue-digital conversion; coding errors; encoding; picture
processing; screens (display); visual perception
Other Terms encoding; picture processing; visual perception; digital image
coding; perceptual image quality assessment; video screens;
quantization errors; scale-space coding; quantization;
impairments
ClassCodes A8732S; A4230V; A8732Q; B6140C; B6120B; B7260; B6430; B7500
Article Type Experimental
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3866451
AbstractNos. A91056424; B91033467
ISSN 0277786X
References 23
Country Pub. USA
date 1172
------------------------------------------------------------
Author Brunnstrom, K.; Eklundh, J.-O.; Lindeberg, T.;
Dept. of Numerical Anal. & Comput. Sci., R. Inst. of Technol.,
Stockholm, Sweden
Title On scale and resolution in active analysis of local image
structure
Source First European Conference on Computer Vision; Part: Antibes,
France; Part: 23-27 April 1990;
Sponsored by: INRIA;
Image and Vision Computing;
vol.8, no.4;
Nov. 1990; pp. 289-96
Abstract Focus-of-attention is extremely important in human visual
perception. If computer vision systems are to perform tasks in a
complex, dynamic world they will have to be able to control
processing in a way that is analogous to visual attention in
humans. Problems connected to foveation (examination of selected
regions of the world at high resolution) are examined. In
particular, the problem of finding and classifying junctions from
this aspect is considered. It is shown that foveation as
simulated by controlled, active zooming in conjunction with scale-
space techniques allows for robust detection and classification
of junctions
Thesaurus computer vision
Other Terms scale; resolution; active analysis; local image structure;
human visual perception; computer vision systems; foveation;
active zooming; scale-space techniques; classification
ClassCodes C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Coden IVCODK
Language English
RecordType Conference
ControlNo. 3856950
AbstractNos. C91026335
ISSN 02628856
References 16
U.S. Copyright Clearance Center Code
0262-8856/90/040289-08$3.00
Country Pub. UK
date 1174
------------------------------------------------------------
Author Martens, J.-B.;
Inst. for Perception Res., Eindhoven, Netherlands
Title Application of scale space to image coding
Source IEEE Transactions on Communications;
IEEE Trans. Commun. (USA);
vol.38, no.9;
Sept. 1990; pp. 1585-91
Abstract The continuous formulation of scale space is briefly reviewed. It
is shown that deriving a discrete formulation of scale space
requires the solution to a more general problem; the optimum
approximation of a signal by local patterns. The consequences of
the theory for the Laplacian image pyramid are discussed. A
pyramid coding scheme based on the discrete scale-space
formulation is derived. Preliminary coding results on real images
are presented. Down to 1 b/pixel, the quality of the coded images
is usually very close to that of the originals. Bit rates below 0.
5 b/pixel imply a too coarse quantization, or even deletion, of
the prediction error image at the smallest scale and,
consequently, always result in images that are noticeably unsharp.
In the intermediate region, different degrees of quantization
noise and unsharpness are present. At comparable data rates, the
linear variation coder generates less quantization noise in
uniform regions, while the scale-space coder gives a slightly
better edge reproduction
Thesaurus encoding; filtering and prediction theory; picture processing
Other Terms scale space filtering; image quality; image coding; Laplacian
image pyramid; pyramid coding scheme; discrete scale-space
formulation
ClassCodes B6140C; B6120B; C1250
Article Type Theoretical / Mathematical
Coden IECMBT
Language English
RecordType Journal
ControlNo. 3848128
AbstractNos. B91026543; C91020007
ISSN 00906778
References 18
U.S. Copyright Clearance Center Code
0090-6778/90/0900-1585$01.00
Country Pub. USA
date 1179
------------------------------------------------------------
Author Etoh, M.; Tomono, A.; Kishino, F.;
ATR Commun. Syst. Res. Lab., Kyoto, Japan
Title Stereo-based description by generalized cylinder complexes from
occluding contours
Source Transactions of the Institute of Electronics, Information and
Communication Engineers D-II;
Trans. Inst. Electron. Inf. Commun. Eng. D-II (Japan);
vol.J73D-II, no.9;
Sept. 1990; pp. 1402-12
Abstract Three-dimensional description of a straight homogeneous
generalized cylinder (SHGC) using axis-based stereo, and a
contour line segmentation method are described. In this approach,
stereo contour images are used. A pair of line segments are
extracted assuming that they are the extremal contour of an SHGC.
The axis of the SHGC's contour image is determined as smoothed
local symmetry (SLS) of the line segments. The SHGC's axis is
recovered by the stereo match of axes of SLS. For the line
segmentation, an interval tree structure is built taking feature
points as the curvature extrema using scale-space analysis. As a
result, actual cylindrical objects are described as three-
dimensional axes
Thesaurus computer vision; computerised pattern recognition
Other Terms generalized cylinder complexes; occluding contours; straight
homogeneous generalized cylinder; axis-based stereo; contour
line segmentation method; stereo contour images; extremal
contour; smoothed local symmetry; interval tree structure;
feature points; curvature extrema; scale-space analysis;
cylindrical objects; three-dimensional axes
ClassCodes C5260B; C1250
Article Type Theoretical / Mathematical; Experimental
Coden DTGDE7
Language Japanese
RecordType Journal
ControlNo. 3816935
AbstractNos. C91016062
References 19
Country Pub. Japan
date 1179
------------------------------------------------------------
Author Schenk, T.; Jin-Cheng Li; Toth, C.K.;
Dept. of Geodetic Sci. & Surveying, Ohio State Univ., Columbus,
OH, USA
Title Hierarchical approach to reconstruct surfaces by using
iteratively rectified imagery
Source Close-Range Photogrammetry Meets Machine Vision; Part: Zurich,
Switzerland; Part: 3-7 Sept. 1990;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1395, pt.1;
1990; pp. 464-70
Abstract A new approach to reconstruct the three-dimensional surface of
the object space from digital image is described. All the object
points obtained by an automatic orientation procedure lead to a
first approximation of the surface. Edges are computed for one
image and matched to the other image by grey level correlation or
least-squares matching through the scale space. To every discrete
step in the scale space there exists the digital stereopair
(image pyramid), the corresponding surface (digital elevation
model DEM) and the warped images. The warped images in this
discrete scale space representation correspond to digital
orthophotos obtained from the DEMs that result from matching the
image pyramid. The authors propose to use the warped images on
every successive level in the image pyramid in order to reduce
the foreshortening problems associated with any area-based
matching method. The method and some experimental results are
reported
Thesaurus computerised picture processing; iterative methods; least
squares approximations
Other Terms hierarchical system; iteratively rectified imagery; three-
dimensional surface; object space; digital image; automatic
orientation procedure; grey level correlation; least-squares
matching; digital stereopair; image pyramid; digital elevation
model; warped images; digital orthophotos; area-based matching
ClassCodes A4230V; A0260; B6140C; B0290F; C5260B; C7410H; C4130
Article Type Practical; Experimental
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3813144
AbstractNos. A91022158; B91011222; C91016025
ISSN 0277786X
References 9
Country Pub. USA
date 1179
------------------------------------------------------------
Author Lindeberg, T.; Eklundh, J.-O.;
Comput. Vision & Active Perception Lab., Inst. of Technol.,
Stockholm, Sweden
Title Construction of a scale-space primal sketch
Source BMVC90 Proceedings of the British Machine Vision Conference; Part:
Oxford, UK; Part: 24-27 Sept. 1990;
Oxford, UK;
BMVC 90;
xxiii+426;
1990; pp. 97-102
Abstract The authors present a multi-scale representation of grey-level
shape, called scale-space primal sketch that makes explicit
features in scale-space as well as the relations between features
at different levels of scale. The representation gives a
qualitative description of the image structure that allows for
extraction of significant image structure-stable scales and
regions of interest-in a solely bottom-up data-driven manner.
Hence, it can be seen as preceding further processing, which can
then be properly tuned. Experiments on real imagery demonstrate
that the proposed theory gives perceptually intuitive results
Thesaurus computer vision; computerised pattern recognition; computerised
picture processing
Other Terms scale space representation; multi-scale representation; grey-
level shape; scale-space primal sketch; image structure; real
imagery
ClassCodes B6140C; C5260B; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3811153
AbstractNos. B91011311; C91009872
References 11
Country Pub. UK
date 1179
------------------------------------------------------------
Author Wilson, R.; spann, M.;
Warwick Univ., Coventry, UK
Title A new approach to clustering
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.23, no.12;
1990; pp. 1413-25
Abstract Estimation theory is used to derive a new approach to the
clustering problem. The new method is a unification of centroid
and mode estimation, achieved by considering the effect of
spatial scale on the estimator. The result is a multiresolution
method which spans a range of spatial scales, giving enhanced
robustness both to noise in the data and to changes of scale in
the data, by using comparison between scales as a test of cluster
validity. Iterative and non-iterative algorithms based on the new
estimator are presented and are shown to be more accurate than
simple scale-space filtering in identifying and locating the
cluster centres from noisy test data. Results from a wide range
of applications are used to illustrate the power and versatility
of the new method
Thesaurus estimation theory; iterative methods; pattern recognition
Other Terms pattern recognition; iterative algorithm; noniterative algorithm
; clustering; spatial scale; multiresolution method
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 3807536
AbstractNos. B91011194; C91007695
ISSN 00313203
References 21
U.S. Copyright Clearance Center Code
0031-3203/90/$3.00+.00
Country Pub. UK
date 1171
------------------------------------------------------------
Author Ueda, N.; Suzuki, S.;
NTT Human Interface Labs., Yokosuka, Japan
Title A matching algorithm of deformed planar curves using multiscale
convex/concave structures
Source Transactions of the Institute of Electronics, Information and
Communication Engineers D-II;
Trans. Inst. Electron. Inf. Commun. Eng. D-II (Japan);
vol.J73D-II, no.7;
July 1990; pp. 992-1000
Abstract This paper proposes a multiscale segment matching method based on
hierarchical convex/concave structures. First, multiscale
representations are obtained using curvature scale space
filtering and then inflection point correspondences are computed
between consecutive smoothed shapes. This correspondence is
useful for decreasing data space and calculation time of the
scale space descriptions. Then the authors define the
dissimilarity between two multiscale segments and optimize total
dissimilarities between two multiscale shapes using a dynamic
programming technique. Therefore, this method, unlike
conventional methods, is applicable to the matching of highly
deformed shapes. Experimental results show the usefulness of the
proposed method
Thesaurus computerised pattern recognition; computerised picture processing
Other Terms deformed planar curves; multiscale segment matching;
hierarchical convex/concave structures; multiscale
representations; curvature scale space filtering; inflection
point correspondences; consecutive smoothed shapes; scale space
descriptions; dissimilarity; multiscale segments; dynamic
programming; deformed shapes
ClassCodes C5260B; C1250
Article Type Theoretical / Mathematical; Experimental
Coden DTGDE7
Language Japanese
RecordType Journal
ControlNo. 3795991
AbstractNos. C91009812
References 4
Country Pub. Japan
date 1177
------------------------------------------------------------
Author Topkar, V.; Kjell, B.; Sood, A.;
George Mason Univ., Fairfax, VA, USA
Title Object detection using scale-space
Source Applications of Artificial Intelligence VIII; Part: Orlando, FL,
USA; Part: 17-19 April 1990;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1293, pt.1;
1990; pp. 2-13
Abstract Scale-space representation is a topic of active research in
computer vision. Most of the work so far has concentrated on
image reconstruction from the scale-space representation. In this
paper the authors discuss the use of scale-space representation
for object detection. They have proposed a model-based approach
and have developed an algorithm to implement it. Channel
integration is the heart of the algorithm and there are a number
of unresolved issues in it. Object detection is possible only if
the objects of interest are different from the noise and clutter
in certain features. The authors have used two different images,
one with good signal to noise ratio and the other with poor
signal to noise ratio. In the first image the distinguishing
feature of the object is its signal strength and in the second
image it is its size. Accordingly, the authors have studied two
approaches to the channel integration: (i) based on the contrast
value and (ii) based on edge focusing and splitting. The results
of both approaches are presented and discussed
Thesaurus computer vision; spatial reasoning
Other Terms object size; image reconstruction; scale-space representation;
object detection; model-based approach; clutter; signal to
noise ratio; signal strength; channel integration; contrast;
edge focusing; splitting
ClassCodes C1250
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3791472
AbstractNos. C91007706
ISSN 0277786X
References 13
Country Pub. USA
date 1174
------------------------------------------------------------
Author Young Won Lim; Sang Uk Lee;
Dept. of Control & Instrumentation Eng., Seoul Nat. Univ., South
Korea
Title On the color image segmentation algorithm based on the
thresholding and the fuzzy c-means techniques
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.23, no.9;
1990; pp. 935-52
Abstract A segmentation algorithm for color images based on the
thresholding and the fuzzy c-means (FCM) techniques is presented.
The scale-space filter is used as a tool for analyzing the
histograms of three color components. The methodology uses a
coarse-fine concept to reduce the computational burden required
for the FCM. The coarse segmentation attempts to segment coarsely
using the thresholding technique, while the fine segmentation
assigns the pixels, which remain unclassified after the coarse
segmentation, to the closest class using the FCM. Attempts also
have been made to compare the performance of the proposed
algorithm with other existing algorithms-Ohlander's, Rosenfeld's,
and Bezdek's. Intensive computer simulation has been performed
and the results are discussed in this paper
Thesaurus computerised picture processing; filtering and prediction theory;
fuzzy set theory
Other Terms computerised picture processing; color image segmentation
algorithm; thresholding; fuzzy c-means; scale-space filter;
coarse-fine concept
ClassCodes B6140C; B0250; C1250; C5260B; C1160
Article Type Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 3785592
AbstractNos. B91004036; C91000884
ISSN 00313203
References 23
U.S. Copyright Clearance Center Code
0031-3203/90/$3.00+.00
Country Pub. UK
date 1171
------------------------------------------------------------
Author Vaezi, M.; Bavarian, B.;
Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
Title Composite-scale Gaussian filtering
Source Conference Record. Twenty-Third Asilomar Conference on Signals,
Systems ands Computers (IEEE Cat. No.89-CH2836-5); Part: Pacific
Grove, CA, USA; Part: 30 Oct.-1 Nov. 1989;
Sponsored by: IEEE; Naval Postgraduate Sch.; San Jose State Univ;
San Jose, CA, USA;
Maple Press;
2 vol. xix+1064;
1989; pp. 741-3 vol.2
Editor Chen, R.R.
Abstract An approach to the scale-space Gaussian filtering is described.
This technique involves the use of a nonlinear function of input
intensity and its first (and second) derivative(s) for the scale
of the Gaussian filter where image smoothing and the correct
space location of the zero crossings in an image are detected in
one pass of convolution. The possible mathematical structure
describing the optimality of this method is discussed.
Illustrative examples are presented
Thesaurus computerised picture processing; digital filters; filtering and
prediction theory
Other Terms input intensity nonlinear function; digital image filters;
scale-space Gaussian filtering; image smoothing; correct space
location; zero crossings; convolution
ClassCodes B6140; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3776256
AbstractNos. B90078005; C91001081
References 6
U.S. Copyright Clearance Center Code
23ACSSC-12/89/0741$1.00
Country Pub. USA
date 1167
------------------------------------------------------------
Author Acharya, R.;
Electr. & Comput. Eng., State Univ. of New York, Buffalo, NY, USA
Title Multidimensional image analysis and mathematical morphology
Source Sixth Multidimensional Signal Processing Workshop (Cat. No.
89TH0290-7); Part: Pacific Grove, CA, USA; Part: 6-8 Sept. 1989;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
242;
1989; pp. 203
Abstract Summary form only given. Multidimensional operators based on
mathematical morphology have been proposed for image segmentation.
Mathematical morphology is basically a set theory. It provides
the concept of a structuring element to probe the image with
arbitrary geometric patterns, in order to capture the topological
properties of the image. The classical operators have been
extended to multidimensions. A morphological approach to scale-
space filtering has been developed. Multiscale morphological
openings that nonlinearly smooth the image without blurring the
features (edges) have been used. The approach has been formulated
within the framework of alternating sequential filters (ASF)
Thesaurus filtering and prediction theory; picture processing; set theory
Other Terms multiscale morphological openings; multidimensional operators;
mathematical morphology; image segmentation; set theory;
arbitrary geometric patterns; topological properties; scale-
space filtering; alternating sequential filters
ClassCodes B6140C; B0250; C1250; C1160
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3763813
AbstractNos. B90078185; C90067795
References 0
Country Pub. USA
date 1166
------------------------------------------------------------
Author Perona, P.;
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley,
CA, USA
Title Anisotropic diffusion processes in early vision
Source Sixth Multidimensional Signal Processing Workshop (Cat. No.
89TH0290-7); Part: Pacific Grove, CA, USA; Part: 6-8 Sept. 1989;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
242;
1989; pp. 68
Abstract Summary form only given. Images often contain information at a
number of different scales of resolution, so that the definition
and generation of a good scale space is a key step in early
vision. A scale space in which object boundaries are respected
and smoothing only takes place within these boundaries has been
defined that avoids the inaccuracies introduced by the usual
method of low-pass-filtering the image with Gaussian kernels. The
new scale space is generated by solving a nonlinear diffusion
differential equation forward in time (the scale parameter). The
original image is used as the initial condition, and the
conduction coefficient c(x, y, t) varies in space and scale as a
function of the gradient of the variable of interest (e.g. the
image brightness). The algorithms are based on comparing the
local values of different diffusion processes running in parallel
on the same image
Thesaurus picture processing
Other Terms analog networks; digital architectures; edge detection; image
compression; parallel computation structure; anisotropic
diffusion process; early vision; scale space; object boundaries
; nonlinear diffusion differential equation; initial condition;
conduction coefficient; gradient; image brightness; algorithms
ClassCodes B6140C
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3763726
AbstractNos. B90078151
References 0
Country Pub. USA
date 1166
------------------------------------------------------------
Author Besslich, P.W.; Forgber, E.;
Dept. of Electr. Eng., Bremen Univ., West Germany
Title Model-based 2D edge detection using bottom-up strategy
Source Sixth Multidimensional Signal Processing Workshop (Cat. No.
89TH0290-7); Part: Pacific Grove, CA, USA; Part: 6-8 Sept. 1989;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
242;
1989; pp. 30-1
Abstract Summary form only given. It has been shown that a bottom-up
strategy using an improved version of the optimized 2D edge
filter fits the requirements of edge detection in real-world 2D
images better than the top-down approach. The results are
obtained by first operating on the full resolution, gradually
restricting it to improve detection capabilities. The 2D filter
has been applied to a bottom-up multiresolution edge detection
scheme. All contour segments are registered. The behavior is
observed while a fine-to-coarse tracing is performed, and the
segments are classified as to whether they carry relevant
information or not. The optimal edge detector has been tested
using two strategies: a top-down procedure and the bottom-up
scale-space scheme. While the computational burden is the same in
both cases, the bottom-up approach provides considerable
improvement in noise suppression and always detects the full
length of a contour as obtained at the finest scale
Thesaurus computerised pattern recognition; computerised picture processing
; filtering and prediction theory; interference suppression
Other Terms optimized 2D edge filter; bottom-up multiresolution edge
detection scheme; contour segments; fine-to-coarse tracing;
top-down procedure; bottom-up scale-space scheme; noise
suppression
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3763708
AbstractNos. B90078144; C90067768
References 3
Country Pub. USA
date 1166
------------------------------------------------------------
Author Zuerndorfer, B.; Wakefield, G.H.;
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor,
MI, USA
Title Extensions of scale-space filtering to machine-sensing systems
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.12, no.9;
Sept. 1990; pp. 868-82
Abstract Major components of scale-space theory are Gaussian filtering,
and the use of zero-crossing thresholders and Laplacian operators.
Properties of scale-space filtering may be useful for data
analysis in multiresolution machine-sensing systems. However,
these systems typically violate the Gaussian filter assumption,
and often the data analyses used (e.g. trend analysis and
classification) are not consistent with zero-crossing
thresholders and Laplacian operators. The authors extend the
results of scale-space theory to include these more general
conditions. In particular, it is shown that relaxing the
requirement of linear scaling allows filters to have non-Gaussian
spatial characteristics, and that relaxing of the scale
requirements (s to 0) of the impulse response allows the use of
scale-space filters with limited frequency support (i.e.
bandlimited filters). Bandlimited scale-space filters represent
an important extension of scale-space analysis for machine sensing
Thesaurus filtering and prediction theory; pattern recognition; picture
processing
Other Terms image sensing; machine vision; scale-space filtering; data
analysis; multiresolution machine-sensing systems; zero-
crossing thresholders; Laplacian operators
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3758654
AbstractNos. B90078048; C90067694
ISSN 01628828
References 18
U.S. Copyright Clearance Center Code
0162-8828/90/0900-0868$01.00
Country Pub. USA
date 1179
------------------------------------------------------------
Author Morita, S.; Kawashima, T.; Aoki, Y.;
Fac. of Eng., Hokkaido Univ., Sapporo, Japan
Title Pattern matching of 2-D shape using hierarchical description
Source Transactions of the Institute of Electronics, Information and
Communication Engineers D-II;
Trans. Inst. Electron. Inf. Commun. Eng. D-II (Japan);
vol.J73D-II, no.5;
May 1990; pp. 717-27
Abstract Introduces a hierarchical description method of two-dimensional
shapes suited for pattern matching. In the method, a shape is
described as a string of scale-filtered line segments called the
basic codon combination and is structured as a tree of segments
along coarse-to-fine scale-space analysis. With the description,
a compact database is created for similar shapes, because trees
overlap at the coarse level. Using the database, analysis and
matching of the tree structure is efficiently performed in a top-
down form. Experimental results show that the system recognizes
the target shape efficiently even if a shape is skewed or occluded
Thesaurus computerised pattern recognition; database management systems;
trees (mathematics)
Other Terms top-down analysis; skewed shapes; occluded shapes;
hierarchical description; two-dimensional shapes; pattern
matching; string; scale-filtered line segments; basic codon
combination; tree; coarse-to-fine scale-space analysis;
compact database
ClassCodes C1250; C5530
Article Type Practical; Experimental
Coden DTGDE7
Language Japanese
RecordType Journal
ControlNo. 3749821
AbstractNos. C90067737
References 15
Country Pub. Japan
date 1175
------------------------------------------------------------
Author Saund, E.;
Xerox Palo Alto Res. Center, CA, USA
Title Symbolic construction of a 2-D scale-space image
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.12, no.8;
Aug. 1990; pp. 817-30
Abstract A symbolic approach to constructing a multiscale primitive shape
description to 2-D binary (silhouette) shape images is presented.
In contrast to contour or region smoothing techniques, grouping
operations are performed over collections of tokens residing on a
scale-space blackboard. Two types of grouping operations are
identified that, respectively, aggregate edge primitives at one
scale into edge primitives at a coarser scale and group edge
primitives into partial-region assertions, including curved
contours, primitive corners, and bars. Procedures to perform
these computations are presented
Thesaurus pattern recognition; picture processing
Other Terms pattern recognition; picture processing; 2-D scale-space image;
multiscale primitive shape description; grouping operations;
edge primitives; partial-region assertions; curved contours;
primitive corners; bars
ClassCodes B6140C; C1250
Article Type Practical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3746886
AbstractNos. B90071185; C90067691
ISSN 01628828
References 35
U.S. Copyright Clearance Center Code
0162-8828/90/0800-0817$01.00
Country Pub. USA
date 1178
------------------------------------------------------------
Author Jepson, A.D.; Fleet, D.J.;
Dept. of Comput. Sci., Toronto Univ., Ont., Canada
Title Scale-space singularities
Source Computer Vision - ECCV 90. First European Conference on Computer
Vision Proceedings; Part: Antibes, France; Part: 23-27 April
1990;
Sponsored by: INRIA;
Berlin, West Germany;
Springer-Verlag;
xii+618;
1990; pp. 50-5
Editor Faugeras, O.
Abstract Phase-based techniques for the measurement of binocular disparity
and image velocity are encouraging, especially because of the
stability of band-pass phase information with respect to
deviations from image translation that are typical in projections
of 3-D scenes. Despite this stability, phase is unreliable in the
neighbourhoods of phase singularities. This instability is
described, and it is shown that singularity neighbourhoods may be
detected using simple constraints on the local frequency and the
amplitude of the filter output. Finally, these results are
discussed briefly in the context of binocular disparity
measurement
Thesaurus computer vision; computerised picture processing
Other Terms phase-based techniques; image velocity measurement; 3D scene
projections; stability; band-pass phase information; deviations
; image translation; phase singularities; instability;
singularity neighbourhoods; local frequency; amplitude; filter
output; binocular disparity measurement
ClassCodes B6140C; C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3742851
AbstractNos. B90071249; C90061261
ISBN or SBN 3 540 52522 X
References 12
Country Pub. West Germany
date 1174
------------------------------------------------------------
Author Perona, P.; Malik, J.;
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley,
CA, USA
Title Scale-space and edge detection using anisotropic diffusion
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.12, no.7;
July 1990; pp. 629-39
Abstract A new definition of scale-space is suggested, and a class of
algorithms used to realize a diffusion process is introduced. The
diffusion coefficient is chosen to vary spatially in such a way
as to encourage intraregion smoothing rather than interregion
smoothing. It is shown that the 'no new maxima should be
generated at coarse scales' property of conventional scale space
is preserved. As the region boundaries in the approach remain
sharp, a high-quality edge detector which successfully exploits
global information is obtained. Experimental results are shown on
a number of images. Parallel hardware implementations are made
feasible because the algorithm involves elementary, local
operations replicated over the image
Thesaurus filtering and prediction theory; pattern recognition; picture
processing
Other Terms parallel processing; picture processing; edge detection;
anisotropic diffusion; scale-space; intraregion smoothing
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical; Experimental
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3735403
AbstractNos. B90071174; C90061167
ISSN 01628828
References 22
U.S. Copyright Clearance Center Code
0162-8828/90/0700-0629$01.00
Country Pub. USA
date 1177
------------------------------------------------------------
Author Brunnstrom, K.; Eklundh, J.-O.; Lindeberg, T.;
Comput, Vision & Associative Pattern Process. Lab., R. Inst. of
Technol., Stockholm, Sweden
Title On scale and resolution in the analysis of local image structure
Source Computer Vision - ECCV 90. First European Conference on Computer
Vision Proceedings; Part: Antibes, France; Part: 23-27 April
1990;
Sponsored by: INRIA;
Berlin, West Germany;
Springer-Verlag;
xii+618;
1990; pp. 3-12
Editor Faugeras, O.
Abstract Focus-of-attention is extremely important in human visual
perception. If computer vision systems are to perform tasks in a
complex, dynamic world they will have to be able to control
processing in a way that is analogous to visual attention in
humans. The paper investigates problems in connection with
foveation, that is examining selected regions of the world at
high resolution. It considers the problem of finding and
classifying junctions from this aspect. It shows that foveation
as simulated by controlled, active zooming in conjunction with
scale-space techniques allows robust detection and classification
of junctions
Thesaurus computer vision; computerised picture processing
Other Terms focus of attention; robust classification; scale; resolution;
local image structure; human visual perception; computer vision
systems; visual attention; foveation; selected regions; world;
high resolution; junctions; active zooming; scale-space;
robust detection
ClassCodes C5260B
Article Type Practical
Language English
RecordType Conference
ControlNo. 3731228
AbstractNos. C90063685
ISBN or SBN 3 540 52522 X
References 15
Country Pub. West Germany
date 1174
------------------------------------------------------------
Author Wada, T.; Yi He Gu; Sato, M.;
Res. Lab. of Precision Machinery & Electron., Tokyo Inst. of
Technol., Yokohama, Japan
Title Scale-space filtering for periodic waveforms
Source Transactions of the Institute of Electronics, Information and
Communication Engineers D-II;
Trans. Inst. Electron. Inf. Commun. Eng. D-II (Japan);
vol.J73D-II, no.4;
April 1990; pp. 544-52
Abstract Scale-space filtering is a multi-resolution filtering technique,
which has suitable properties for a hierarchical description of
waveform. The most important property is that the number of zero
crossings will never increase, while increasing the scale-
parameter. It is called the monotonicity of zero crossings. The
authors construct the scale-space filtering for periodic
waveforms to hold the monotonicity. The derived filtering kernel
is the elliptic theta function of the third kind I/sub 3/. The
basic properties of this filtering is cleared. Some examples of
structural analysis are shown, and the basic differences between
periodic scale-space filtering and non-periodic are discussed
Thesaurus filtering and prediction theory; waveform analysis
Other Terms hierarchical waveform description; multi-resolution filtering;
zero crossings; periodic waveforms; elliptic theta function
ClassCodes B6140; C1260
Article Type Theoretical / Mathematical
Coden DTGDE7
Language Japanese
RecordType Journal
ControlNo. 3727560
AbstractNos. B90063596; C90061446
References 8
Country Pub. Japan
date 1174
------------------------------------------------------------
Author Etoh, M.; Tomono, A.; Kobayashi, Y.;
ATR Commun. Syst. Res. Lab., Kyoto, Japan
Title Cylindrical part recognition in occluding contours
Source Intelligent Robots and Computer Vision VIII: Algorithms and
Techniques; Part: Philadelphia, PA, USA; Part: 6-10 Nov. 1989;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1192, pt.1;
1990; pp. 353-62
Abstract Three-dimensional reconstruction method of a straight homogeneous
generalized cylinder model using 'axis-based stereo', and contour
line segmentation method are described. To achieve the axis-based
stereo matching, stereo contour images are used. In each contour
image, a pair of contour line segments are assumed to be the
extremal contour of a cylinder and are interpreted as a 'ribbon'.
A pair of ribbons over the stereo contour images are interpreted
as a 'cylinder'. The cylinder's axis is determined by the stereo
match of two ribbon's axes in space. For the line segmentation,
an interval tree structure is built taking feature points as the
curvature extrema using scale-space analysis, and splitting the
feature points' interval recursively to satisfy a line regularity
Thesaurus computer vision; computerised pattern recognition; computerised
picture processing
Other Terms 3D image reconstruction; occluding contour recognition;
computerised picture processing; pattern recognition; cylinder
model; contour line segmentation; stereo matching; tree
structure; feature points; curvature; scale-space analysis
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3698298
AbstractNos. B90056884; C90055154
ISSN 0277786X
References 18
Country Pub. USA
date 1168
------------------------------------------------------------
Author Meer, P.; Sher, C.A.; Rosenfeld, A.;
Center for Autom. Res., Maryland Univ., College Park, MD, USA
Title The chain pyramid: hierarchical contour processing
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.12, no.4;
April 1990; pp. 363-76
Abstract A novel hierarchical approach toward fast parallel processing of
chain-codable contours is presented. The environment, called the
chain pyramid, is similar to a regular nonoverlapping image
pyramid structure. The artifacts of contour processing on
pyramids are eliminated by a probabilistic allocation algorithm.
Building of the chain pyramid is modular, and for different
applications new algorithms can be incorporated. Two applications
are described: smoothing of multiscale curves and gap bridging in
fragmented data. The latter is also employed for the treatment of
branch points in the input contours. A preprocessing module
allowing the application of the chain pyramid to raw edge data is
also described. The chain pyramid makes possible fast,
O(log(image/sub -/size)), computation of contour representation
in discrete scale-space
Thesaurus computerised picture processing; parallel processing
Other Terms computerised picture processing; chain pyramid; hierarchical
contour processing; parallel processing; chain-codable contours;
probabilistic allocation algorithm; smoothing; multiscale
curves; gap bridging; fragmented data; raw edge data
ClassCodes C5260B
Article Type Practical; Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3663309
AbstractNos. C90046136
ISSN 01628828
References 33
U.S. Copyright Clearance Center Code
0162-8828/99/0400-0363$01.00
Country Pub. USA
date 1174
------------------------------------------------------------
Author Siebert, J.P.; Urquhart, C.W.;
BBN Syst. & Technol., Heriot-Watt Res. Park, Edinburgh, UK
Title Active stereo: texture enhanced reconstruction
Source Electronics Letters;
Electron. Lett. (UK);
vol.26, no.7;
29 March 1990; pp. 427-30
Abstract An experiment is presented that combines active and passive
vision techniques. The authors have demonstrated that it is
possible to recover dense range map information from stereograms
of scenes bathed in random noise 'textured light' by employing
scale-space signal matching techniques
Thesaurus computer vision; computerised picture processing; texture
Other Terms active stereo; CCD camera; random noise textured light;
multiscale signed matches; texture enhanced reconstruction;
passive vision; dense range map information; stereograms;
scale-space signal matching techniques
ClassCodes A4230V; B6140C; C1250
Article Type Experimental
Coden ELLEAK
Language English
RecordType Journal
ControlNo. 3652112
AbstractNos. A90080563; B90045575; C90038342
ISSN 00135194
References 3
U.S. Copyright Clearance Center Code
0013-5194/90/$3.00+0.00
Country Pub. UK
date 1173
------------------------------------------------------------
Author Lindeberg, T.;
Comput. Vision & Associative Pattern Process. Lab., R. Inst. of
Technol., Stockholm, Sweden
Title Scale-space for discrete signals
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.12, no.3;
March 1990; pp. 234-54
Abstract A basic and extensive treatment of discrete aspects of the scale-
space theory is presented. A genuinely discrete scale-space
theory is developed and its connection to the continuous scale-
space theory is explained. Special attention is given to
discretization effects, which occur when results from the
continuous scale-space theory are to be implemented
computationally. The 1D problem is solved completely in an
axiomatic manner. For the 2D problem, the author discusses how
the 2D discrete scale space should be constructed. The main
results are as follows: the proper way to apply the scale-space
theory to discrete signals and discrete images is by
discretization of the diffusion equation, not the convolution
integral; the discrete scale space obtained in this way can be
described by convolution with the kernel, which is the discrete
analog of the Gaussian kernel, a scale-space implementation based
on the sampled Gaussian kernel might lead to undesirable effects
and computational problems, especially at fine levels of scale;
the 1D discrete smoothing transformations can be characterized
exactly and a complete catalogue is given; all finite support 1D
discrete smoothing transformations arise from repeated averaging
over two adjacent elements (the limit case of such an averaging
process is described); and the symmetric 1D discrete smoothing
kernels are nonnegative and unimodal, in both the spatial and the
frequency domain
Thesaurus discrete systems; signal processing
Other Terms signal processing; nonnegative kernels; unimodal kernels;
spatial domain; discrete signals; discrete scale-space theory;
diffusion equation; Gaussian kernel; discrete smoothing
transformations; frequency domain
ClassCodes C1260
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3641638
AbstractNos. C90038539
ISSN 01628828
References 23
U.S. Copyright Clearance Center Code
0162-8828/90/0300-0234$01.00
Country Pub. USA
date 1173
------------------------------------------------------------
Author Leymarie, F.; Levine, M.D.;
McGill Res. Center for Intelligent Mach., McGill Univ., Montreal,
Que., Canada
Title Shape features using curvature morphology
Source Visual Communications and Image Processing IV; Part:
Philadelphia, PA, USA; Part: 8-10 Nov. 1989;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1199, pt.1;
1989; pp. 390-401 pt.1
Abstract The authors briefly present a scheme for obtaining the discrete
curvature function of planar contours based on the chain-code
representation of a boundary. They propose a method for
extracting important features from the curvature function such as
extrema or peaks, and segments of constant curvature, using
mathematical morphological operations on functions. On the basis
of these morphological operations, they suggest a new scale-space
representation for curvature named the Morphological Curvature
Scale-Space. Advantages over the usual scale-space approaches are
shown
Thesaurus computer vision; curvature measurement
Other Terms shape feature extraction; computer vision; curvature morphology;
discrete curvature function; chain-code representation;
mathematical morphological operations; scale-space representation
ClassCodes C1250; C1160; C5260B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3617146
AbstractNos. C90031701
ISSN 0277786X
References 34
Country Pub. USA
date 1168
------------------------------------------------------------
Author Hummel, R.; Moniot, R.;
Courant Inst. of Math. Sci., New York Univ., NY, USA
Title Reconstructions from zero crossings in scale space
Source IEEE Transactions on Acoustics, Speech and Signal Processing;
IEEE Trans. Acoust. Speech Signal Process. (USA);
vol.37, no.12;
Dec. 1989; pp. 2111-30
Abstract In computer vision, the one-parameter family of images obtained
from the Laplacian-of-a-Gaussian-filtered version of the image,
parameterized by the width of the Gaussian, has proved to be a
useful data structure for the extraction of feature data. In
particular, the zero crossings of this so-called scale-space data
are associated with edges and have been proposed by D. Marr
(1982) and others as the basis of a representation of the image
data. The question arises as to whether the representation is
complete and stable. The authors survey some of the studies and
results related to these questions as well as several studies
that attempt reconstructions based on this or related
representations. They formulate a novel method for reconstruction
from zero crossings in scale space that is based on minimizing
equation error, and they present results showing that the
reconstruction is possible but can be unstable. They further show
that the method applies when gradient data along the zero
crossings are included in the representation, and they
demonstrate empirically that the reconstruction is then stable
Thesaurus computer vision; computerised picture processing; filtering and
prediction theory
Other Terms image reconstruction; picture processing; zero crossings;
scale space; computer vision; one-parameter family; images;
Laplacian-of-a-Gaussian-filtered; data structure; feature data;
equation error
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Coden IETABA
Language English
RecordType Journal
ControlNo. 3606735
AbstractNos. B90030589; C90024515
ISSN 00963518
References 41
U.S. Copyright Clearance Center Code
0096-3518/89/1200-2111$01.00
Country Pub. USA
date 1169
------------------------------------------------------------
Author Parvin, B.; Medioni, G.;
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles,
CA, USA
Title A constraint satisfaction network for matching 3D objects
Source IJCNN: International Joint Conference on Neural Networks (Cat. No.
89CH2765-6); Part: Washington, DC, USA; Part: 18-22 June 1989;
Sponsored by: IEEE;
New York, NY, USA;
IEEE TAB Neural Network Committee;
2 vol. (790+646);
1989; pp. 281-6 vol.2
Abstract A new approach is presented for matching visible surfaces of 3D
objects using a constraint satisfaction network. This in turn
provides the necessary basis for volumetric reconstruction from
multiple views. By matching, the authors mean both to establish
correspondence between individual faces and to compute 3D
transform that would bring one in correspondence with the other.
Toward this goal, constraints at three different levels of
complexities are specified to produce stable and coherent
assignments. The constraint satisfaction is implemented as a
Hopfield network with an appropriate energy functional and
minimized using simulated annealing. The system extracts objects
faces by computing their bounding contours with adaptive scale
space filtering. This process identifies important surface
features such as jumps or occluding boundaries and creases. The
pointwise feature descriptors are then linked, and an attributed
graph is derived to represent the object. The nodes in the graph
represent geometric surface features, and the links in the graph
represent the relationship between adjacent surfaces. The authors
present results on real images
Thesaurus filtering and prediction theory; neural nets; pattern
recognition; transforms
Other Terms pattern recognition; neural nets; 3D objects matching;
constraint satisfaction network; volumetric reconstruction;
multiple views; 3D transform; Hopfield network; simulated
annealing; adaptive scale space filtering; jumps; occluding
boundaries; creases; pointwise feature descriptors; attributed
graph
ClassCodes B6140C; B0230; C1250; C1260; C1130; C1230
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3601690
AbstractNos. B90023846; C90024628
References 23
Country Pub. USA
date 1163
------------------------------------------------------------
Author Blostein, D.; Ahuja, N.;
Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
Title Shape from texture: integrating texture-element extraction and
surface estimation
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.11, no.12;
Dec. 1989; pp. 1233-51
Abstract A method is presented for identifying texture elements while
simultaneously recovering the orientation of textured surfaces. A
multiscale region detector, based on measurements in a Del /sup
2/G (Laplacian-of-Gaussian) scale space, is used to construct a
set of candidate texture elements. True elements are selected
from the set of candidate elements by finding the planar surface
that best predicts the observed areas of the latter. Results are
shown for a variety of natural textures, including waves, flowers,
rocks, clouds, and dirt clods
Thesaurus pattern recognition; picture processing
Other Terms surface orientation estimation; texture element identification;
Laplacian-of-Gaussian scale space; Del /sup 2/G scale space;
texture-element extraction; multiscale region detector; waves;
flowers; rocks; clouds; dirt clods
ClassCodes C1250
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3572673
AbstractNos. C90018327
ISSN 01628828
References 27
U.S. Copyright Clearance Center Code
0162-8828/89/1200-1233$01.00
Country Pub. USA
date 1169
------------------------------------------------------------
Author Koenderink, J.J.;
Dept. of Med. & Physiol. Phys., Utrecht Univ., Netherlands
Title A hitherto unnoticed singularity of scale-space
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.11, no.11;
Nov. 1989; pp. 1222-4
Abstract A hitherto unnoticed singularity of scale space occurs only at
isolated points in scale space. Thus it does not generically
occur for single images, but it can occur occasionally in members
of time sequences (say). It occurs at those critical points of
the image at which the Laplacean of the illuminance vanishes (a
nongeneric condition). The structure of scale space in an
infinitesimal neighborhood of such a singularity is explored. The
effect of the singularity of mappings between copies of an image
at different levels of resolution is evaluated and checked with a
numerical calculation
Thesaurus pattern recognition; picture processing
Other Terms picture processing; pattern recognition; hitherto unnoticed
singularity; scale-space; time sequences; mappings
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3572670
AbstractNos. B90017119; C90018326
ISSN 01628828
References 6
U.S. Copyright Clearance Center Code
0162-8828/89/1100-1222$01.00
Country Pub. USA
date 1168
------------------------------------------------------------
Author Estola, K.-P.;
Machine Autom. Lab., Tech. Centre of Finland, Tampere, Finland
Title Multirate Gaussian scale-space filtering
Source Eurospeech 89. European Conference on Speech Communication and
Technology; Part: Paris, France; Part: 26-28 Sept. 1989;
Sponsored by: Assoc. Belge des Acousticiens; Assoc. Recherche
Cognitive; Comm. Eur. Communities; et al;
Edinburgh, UK;
CEP Consultants;
2 vol. (xxiii+636+xxi+721);
1989; pp. 625-8 vol.1
Editor Tubach, J.P.; Mariani, J.J.
Abstract This paper proposes multirate signal processing methods for
realizing Gaussian scale-space filtering. The author introduces
new computationally efficient interpolated Gaussian scale-space
filters. Also, the use of decimators together with interpolated
Gaussian filters is considered. The proposed filtering methods
require dramatically less computation than conventional Gaussian
scale-space filtering especially in cases where the scale changes
with an integer factor. The new filters are extremely efficient
when the change in scale is an integer power of two. However,
also more complex scaling factors such as square root 2 can be
efficiently realized
Thesaurus filtering and prediction theory; signal processing
Other Terms multirate Gaussian scale-space filtering; signal processing
methods; decimators
ClassCodes B6140; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3557786
AbstractNos. B90009917; C90011235
References 5
Country Pub. UK
date 1166
------------------------------------------------------------
Author Sato, M.; Wada, T.;
Res. Lab. of Precision Machinery & Electron., Tokyo Inst. of
Technol., Japan
Title Structure line of waveforms and its application
Source Proceedings of 6th Scandinavian Conference on Image Analysis; Part
: Oulu, Finland; Part: 19-22 June 1989;
Sponsored by: Int. Assoc. Pattern Recognition;
Oulu, Finland;
Pattern Recognition Soc. Finland;
2 vol.(xx+1253);
1989; pp. 868-73 vol.2
Editor Pietikainen, M.; Roning, J.
Abstract A structure line is a hierarchical representation of waveforms
based on scale space filtering. Structure line has the same
topological property as a ternary tree, and represents the
hierarchy of convex and concave regions of the waveform. The
authors discuss an application of the structure line to computer
vision. One of the most basic and difficult problems of computer
vision is the reconstruction of the 3-D object from the multi-
viewpoint images. There may be the occlusion of the
characteristic points between the images, then one can't find the
matching pair. So, one should know the occluded regions between
the images before the correspondence process. They investigated
the relation between the morphological transition of the
structure line of the observed images and the transition of the
scene. Then the relation between the transitions of the structure
line and the scene transitions are cleared
Thesaurus computer vision; waveform analysis
Other Terms 3D object reconstruction; convex regions; waveforms; scale
space filtering; ternary tree; concave regions; computer vision
; morphological transition; scene transitions
ClassCodes C1250; C1120
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3557471
AbstractNos. C90011057
References 5
Country Pub. Finland
date 1163
------------------------------------------------------------
Author Krozel, J.;
Artificial Intelligence Center, Hughes Res. Labs., Malibu, CA, USA
Title Planning with abstraction: map data feature extraction in scale-
space
Source Applications of Artificial Intelligence VII; Part: Orlando, FL,
USA; Part: 28-30 March 1989;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1095, pt.1;
1989; pp. 25-35
Abstract Autonomous vehicles often perform navigation and path planning
using hierarchical control systems. These systems separate high
and low level reasoning through an abstraction of the planning
problem. For reasoning about terrain information, the author
presents a method of abstraction that retains the finest level of
resolution while progressing through greater levels of
abstraction. Abstraction arises from a continuum of Gaussian
smoothed terrain surfaces, each smoothed surface describes the
terrain at a different scale of abstraction. He refers to this
continuum as scale-space. For each level of abstraction,
important features can be extracted from land elevation data for
planning purposes. He presents this abstraction method, a graph
representation for retaining scale-space information, and
examples of how features from various levels of abstraction
influence planning at different levels of a hierarchical control
system
Thesaurus automatic guided vehicles; computer vision; hierarchical systems
; knowledge based systems
Other Terms autonomous vehicles; abstraction; map data feature extraction
in scale-space; navigation; path planning; hierarchical
control systems; planning problem; reasoning; terrain
information; Gaussian smoothed terrain surfaces; land elevation
data; graph representation
ClassCodes C5260B; C3360; C6170
Article Type Practical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3548555
AbstractNos. C90013567
ISSN 0277786X
References 5
Country Pub. USA
date 1160
------------------------------------------------------------
Author Rueff, M.;
Fraunhofer Inst. for Manuf., Eng. & Autom., Stuttgart, West
Germany
Title Scale space filtering and the scaling regions of fractals
Source From Pixels to Features. Proceedings of a Workshop; Part: Bonas,
France; Part: 22-27 Aug. 1988;
Amsterdam, Netherlands;
North-Holland;
xiii+416;
1989; pp. 49-60
Editor Simon, J.C.
Abstract Fractal dimensions are quantities which have been shown to be
useful in the classification and segmentation of textures with
scaling behaviour. The application of the concept of fractal
analysis to the study of irregular structures is demonstrated by
optical roughness measurements. Problems arising in the numerical
determination of fractal dimensions are briefly mentioned. Scale
space filtering techniques are suggested to overcome some of
these problems which in particular are given with the detection
of the limited scaling regions of natural textures
Thesaurus filtering and prediction theory; fractals; pattern recognition
Other Terms scale space filtering; image analysis; lacunarity; fractals;
classification; segmentation; scaling behaviour; fractal
analysis; irregular structures; optical roughness measurements;
fractal dimensions; natural textures
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3545746
AbstractNos. B90010063; C90005324
References 16
Country Pub. Netherlands
date 1152
------------------------------------------------------------
Author de Vel, O.Y.; Thomas, P.;
Dept. of Comput. Sci., Waikato Univ., Hamilton, New Zealand
Title Multi-transputer system for speech spectrogram processing
Source Centre for Advanced Technology in Telecommunications. Australian
Transputer and OCCAM User Group Conference Proceedings; Part:
Melbourne, Vic., Australia; Part: 6-7 July 1989;
Sponsored by: Centre Adv. Technol.Telecommun;
Melbourne, Vic., Australia;
Centre for Adv. Technol. Telecommun;
ii+193;
1989; pp. 29-39
Abstract A parallel processing system used for the low-level, near-
neighbourhood processing of images is presented. The system
consists of a loosely-coupled two-dimensional quad-connected mesh
network for transputers. It is capable of executing both linear
and nonlinear image processing functions. Example functions
include linear convolution, median filtering, edge detection
using the scale-space technique, and simulated annealing. The
system environment includes downloading/uploading the image and
filter masks, execution timing information, and image display.
Near-linear speed-up performances have been observed for all
image processing functions, the interprocessor communication time
being the dominating limiting factor. The parallel image
processing system has been used for the enhancement and
segmentation of speech spectrograms
Thesaurus computerised picture processing; parallel processing; speech
analysis and processing
Other Terms multi-transputer system; image downloading; image uploading;
image enhancement; image segmentation; speech spectrogram
processing; parallel processing system; near-neighbourhood
processing; loosely-coupled two-dimensional quad-connected mesh
network; image processing functions; linear convolution;
median filtering; edge detection; scale-space technique;
simulated annealing; system environment; filter masks;
execution timing information; image display; speed-up
performances; interprocessor communication time
ClassCodes B6140C; B6130; C5260B; C5585
Article Type Practical
Language English
RecordType Conference
ControlNo. 3533692
AbstractNos. B90003028; C90007013
References 9
Country Pub. Australia
date 1164
------------------------------------------------------------
Author Granum, E.; Christensen, H.I.;
Inst. of Electron. Syst., Aalborg Univ., Denmark
Title On principles of motion analysis in real time
Source Image Processing II; Part: Hamburg, West Germany; Part: 19-21
Sept. 1988;
Sponsored by: Eur. Phys. Soc.; Eur. Federation for Appl. Opt.;
SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1027;
1989; pp. 113-20
Abstract A number of motion analysis methods are reviewed and evaluated
with regard to dependency on supplementary processing and with
regard to current potential for real time application. Problems
of ambiguity and noise are considered. Image differencing and the
low and high level token matching approaches are only methods
considered realistic for real time operation. Aspects of higher
level motion analysis are discussed, and the essence put into a
scheme for a model driven approach to real time function. A high
level token matching version of the model driven scheme has been
implemented, and its basic performance was demonstrated on data
with occlusions. Although under conditions of a constraint
scenario, real time motion analysis on computer is feasible
without the need for very sophisticated hardware. A scale space
extension to the implementation was demonstrated, to provide a
potential approach for description and analysis of composite
motion patterns
Thesaurus computer vision; computerised picture processing
Other Terms low level token matching; image differencing; computerised
picture processing; motion analysis; real time; high level
token matching; model driven scheme; scale space extension;
composite motion patterns
ClassCodes C5260B; C7410F
Article Type Practical; Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3526180
AbstractNos. C90006901
ISSN 0277786X
References 41
Country Pub. USA
date 1153
------------------------------------------------------------
Author Haglund, L.; Knutsson, H.; Granlund, G.H.;
Comput. Vision Lab., Linkoping Univ., Sweden
Title Scale analysis using phase representation
Source Proceedings of 6th Scandinavian Conference on Image Analysis; Part
: Oulu, Finland; Part: 19-22 June 1989;
Sponsored by: Int. Assoc. Pattern Recognition;
Oulu, Finland;
Pattern Recognition Soc. Finland;
2 vol.(xx+1253);
1989; pp. 1118-25 vol.2
Editor Pietikainen, M.; Roning, J.
Abstract Scale analysis and description has over the last years become one
of the major research fields in image processing. There are two
main reasons for this. A single filter has a particular limited
pass band which may or may not be tuned to the different sized
objects to be described. Secondly, size or scale is a descriptive
feature in its own right. All of this requires the integration of
measurements from different scales. The paper describes a new
algorithm which detects the scale in which an event appears and
disappears. In this way the scale space is subdivided into a
number of intervals. Within each scale interval a consistency
check is performed to get the certainty of the detection. The
algorithms are shown to be simple operations if a continuous
phase representation is used
Thesaurus filtering and prediction theory; picture processing
Other Terms scale analysis; scale description; phase representation; image
processing; filter; measurements; algorithm; scale space;
scale interval; consistency check; continuous phase
representation
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3524361
AbstractNos. B90003018; C90000476
References 7
Country Pub. Finland
date 1163
------------------------------------------------------------
Author Lindeberg, T.;
Comput. Vision & Associative pattern Processing Lab., R. Inst. of
Technol., Stockholm, Sweden
Title Scale-space for discrete images
Source Proceedings of 6th Scandinavian Conference on Image Analysis; Part
: Oulu, Finland; Part: 19-22 June 1989;
Sponsored by: Int. Assoc. Pattern Recognition;
Oulu, Finland;
Pattern Recognition Soc. Finland;
2 vol.(xx+1253);
1989; pp. 1098-107 vol.2
Editor Pietikainen, M.; Roning, J.
Abstract Addresses the formulation of a scale-space theory for one-
dimensional discrete images. Two main subjects are treated. Which
linear transformations remove structure in the sense that the
number of local extrema (or zero-crossings) in the output image
does not exceed the number of local extrema (or zero-crossings)
in the original image? How should one create a multiresolution
family of representations with the property that an image at a
coarser level of scale never contains more structure than an
image at a finer level of scale? The author proposes that there
is only one reasonable way to define a scale-space for discrete
images comprising a continuous scale parameter, namely by
(discrete) convolution with the family of kernels T(n;t)=e/sup -
t/I/sub n/(t), where I/sub n/ are the modified Bessel functions
of integer order. Similar arguments applied in the continuous
case uniquely lead to the Gaussian kernel
Thesaurus picture processing
Other Terms discrete images; scale-space theory; linear transformations;
local extrema; zero-crossings; output image; continuous scale
parameter; modified Bessel functions; Gaussian kernel
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3524359
AbstractNos. B90003016; C90000474
References 9
Country Pub. Finland
date 1163
------------------------------------------------------------
Author Mussigmann, U.;
Fraunhofer Inst. for Manuf., Eng. & Autom., Stuttgart, West
Germany
Title Texture analysis, fractals and scale space filtering
Source Proceedings of 6th Scandinavian Conference on Image Analysis; Part
: Oulu, Finland; Part: 19-22 June 1989;
Sponsored by: Int. Assoc. Pattern Recognition;
Oulu, Finland;
Pattern Recognition Soc. Finland;
2 vol.(xx+1253);
1989; pp. 987-94 vol.2
Editor Pietikainen, M.; Roning, J.
Abstract The method of scale space filtering has been used till now in
image analysis for the description and recognition of planar
curves and two dimensional shapes. In this paper, the author
presents a new method for the calculation of the fractal
dimension of textures with the help of the scale space filtering.
This fractal dimension is used as a quantitative measure for the
classification and segmentation of textured images
Thesaurus filtering and prediction theory; picture processing
Other Terms picture processing; fractals; scale space filtering; image
analysis; planar curves; textures; classification;
segmentation
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3524344
AbstractNos. B90003001; C90000464
References 16
Country Pub. Finland
date 1163
------------------------------------------------------------
Author Kadirkamanathan, M.; Rayner, P.J.W.;
Dept. of Eng., Cambridge Univ., UK
Title A unified approach to on-line cursive script segmentation and
feature extraction
Source ICASSP-89: 1989 International Conference on Acoustics, Speech and
Signal Processing (IEEE Cat. No.89CH2673-2); Part: Glasgow, UK; P
art: 23-26 May 1989;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
4 vol. 2833;
1989; pp. 1659-62 vol.3
Abstract A stroke segmentation algorithm based on curvature information
processing and scale-space filtering is proposed. The strokes
extracted are very close to strokes described by psychophysicists.
A simple online author-dependent recognition system that uses the
segmentation algorithm as a preprocessing stage is described and
its performance evaluated for handwritten data obtained from five
authors. The segmentation results indicate a performance much
better than that of techniques based on direct estimation of
penspeed or curvature. The scale-space plot of stroke boundaries
also locates many descriptive features detectable in cursive
script, allowing the programmer to choose any desired scale or
scales. Once segmentation is performed, the problem of
recognizing recursive script is not much more difficult than the
problem of recognizing isolated characters. The performance of
the recognition system appears to be better than that of any
cursive script recognition system designed so far, even though
extremely simplifying assumptions have been made in the stroke
matching stage
Thesaurus pattern recognition
Other Terms online cursive script segmentation; feature extraction; stroke
segmentation algorithm; curvature information processing; scale-
space filtering; online author-dependent recognition system;
handwritten data
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3485293
AbstractNos. B89071168; C89059609
References 4
U.S. Copyright Clearance Center Code
CH2673-2/89/0000-1659$01.00
Country Pub. USA
date 1162
------------------------------------------------------------
Author Clippingdale, S.C.; Wilson, R.G.;
Warwick Univ., Coventry, UK
Title Least-squares image estimation on a multiresolution pyramid
Source ICASSP-89: 1989 International Conference on Acoustics, Speech and
Signal Processing (IEEE Cat. No.89CH2673-2); Part: Glasgow, UK; P
art: 23-26 May 1989;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
4 vol. 2833;
1989; pp. 1409-12 vol.3
Abstract A class of linear recursive image estimation methods, based on
multiresolution image representations, is introduced. Although
recursive, the estimators are causal not in the image plane but
in a third dimension, that of the scale index. The estimators are
efficient computationally and are in general suboptimal for a
class of image models based explicitly on the scale-space
underlying the multiresolution description. Methods are also
presented for adapting the estimates to local image structure
across a wide range of scales. The estimates are robust and
outperform many of the techniques reported in the literature in
terms of computational efficiency, signal-to-noise gain, and
subjective appearance. A brief presentation of the theoretical
basis of the methods is followed by experimental results and
conclusions on the potential of the approach
Thesaurus least squares approximations; picture processing
Other Terms multiresolution pyramid; linear recursive image estimation
methods; image plane; scale index; image models;
computational efficiency; signal-to-noise gain
ClassCodes B6140C; B0290F; C1250; C4130
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3485256
AbstractNos. B89071144; C89059595
References 16
U.S. Copyright Clearance Center Code
CH2673-2/89/0000-1409$01.00
Country Pub. USA
date 1162
------------------------------------------------------------
Author Saint-Marc, P.; Chen, J.S.; Medioni, G.;
Dept. of Electr. Eng. & Comput. Sci., Univ. of Southern
California, Los Angeles, CA, USA
Title Adaptive smoothing: a general tool for early vision
Source Proceedings CVPR '89 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.89CH2752-4); Part: San
Diego, CA, USA; Part: 4-8 June 1989;
Sponsored by: IEEE;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xvii+693;
1989; pp. 618-24
Abstract The authors present a method to smooth a signal-whether it is an
intensity image, a range image, or a contour-which preserves
discontinuities and thus facilitates their detection. This is
achieved by repeatedly convolving the signal with a very small
averaging filter modulated by a measure of the signal
discontinuity at each point. This process is related to the
anisotropic diffusion reported by P. Perona and J. Malik (1987)
but it has a much simpler formulation and is not subject to
instability or divergence. Real examples show how this approach
can be applied to the smoothing of various types of signals. The
detected features do not move, and thus no tracking is needed.
The last property makes it possible to derive a novel scale-space
representation of a signal using a small number of scales.
Finally, this process is easily implemented on parallel
architectures: the running time on a 16 K connection machine is
three orders of magnitude faster than on a serial machine
Thesaurus computer vision
Other Terms adaptive smoothing; computer vision; intensity image; range
image; contour; signal discontinuity; scale-space
representation; parallel architectures; 16 K connection machine
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3484911
AbstractNos. B89071136; C89059587
ISBN or SBN 0 8186 1952 x
References 33
U.S. Copyright Clearance Center Code
CH2752-4/89/0000-0618$01.00
Country Pub. USA
date 1163
------------------------------------------------------------
Author Mokhtarian, F.;
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC,
Canada
Title Fingerprint theorems for curvature and torsion zero-crossings
Source Proceedings CVPR '89 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.89CH2752-4); Part: San
Diego, CA, USA; Part: 4-8 June 1989;
Sponsored by: IEEE;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xvii+693;
1989; pp. 269-75
Abstract It has been shown by A.L. Yuille and T. Poggio (1983) that the
scale-space image of a signal determines that signal uniquely up
to constant scaling. Here, generalization of the proof given by
Yuille and Poggio is presented. It is shown that the curvature
scale-space image of a planar curvature determines the curvature
uniquely, up to constant scaling and a rigid motion. The results
show that a 1-D signal can be reconstructed using only one point
from its scale-space image. This is an improvement of the result
obtained by Yuille and Poggio
Thesaurus pattern recognition; picture processing
Other Terms fingerprint theorems; picture processing; pattern recognition;
curvature; zero-crossings; scale-space image; Yuille; Poggio;
constant scaling; rigid motion
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3484884
AbstractNos. B89071111; C89059555
ISBN or SBN 0 8186 1952 x
References 10
U.S. Copyright Clearance Center Code
CH2752-4/89/0000-0269$01.00
Country Pub. USA
date 1163
------------------------------------------------------------
Author Martens, J.B.O.S.; Majoor, G.M.M.;
Inst. for Perception Res., Eindhoven, Netherlands
Title The perceptual relevance of scale-space image coding
Source Signal Processing;
Signal Process. (Netherlands);
vol.17, no.4;
Aug. 1989; pp. 353-64
Abstract The authors summarize the so-called scale-space model and
describe its application to image coding. In the model an image
is passed through Gaussian filters of decreasing bandwidth. The
variation between successively filtered responses is very
systematic, so that little information is needed to pass between
them. Starting from a low resolution version of the original
image, they make a prediction for a higher resolution version.
Only the prediction errors need be transmitted to recover this
higher resolution picture. The process is repeated at a number of
resolutions (called scales) in order to arrive at the original
image. For data-reduction purposes, several approximations of
these prediction errors can be studied. Evaluation of the
resulting coded images is done by means of perceptual experiments.
It is also shown that a one-to-one correspondence can be
established between the different stages of the scale-space coder
and a well-known model of the human visual system that is based
on psychophysical data
Thesaurus data compression; encoding; filtering and prediction theory;
picture processing
Other Terms perceptual relevance; image coding; scale-space model;
Gaussian filters; prediction errors; higher resolution picture;
data-reduction; human visual system; psychophysical data
ClassCodes B6140C; B6120B; C1250
Article Type Theoretical / Mathematical; Experimental
Coden SPRODR
Language English
RecordType Journal
ControlNo. 3483291
AbstractNos. B89071090; C89059507
ISSN 01651684
References 21
U.S. Copyright Clearance Center Code
0165-1684/89/$3.50
Country Pub. Netherlands
date 1165
------------------------------------------------------------
Author Teh, C.-H.; Chin, R.T.;
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Title On the detection of dominant points on digital curves
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.11, no.8;
Aug. 1989; pp. 859-72
Abstract A parallel algorithm is presented for detecting dominant points
on a digital closed curve. The procedure requires no input
parameter and remains reliable even when features of multiple
sizes are present on the digital curve. The procedure first
determines the region of support for each point based on its
local properties, then computes measures of relative significance
(e.g. curvature) of each point, and finally detects dominant
points by a process of nonmaximum suppression. This procedure
leads to the observation that the performance of dominant points
detection depends not only on the accuracy of the measure of
significance, but also on the precise determination of the region
of support. This solves the fundamental problem of scale factor
selection encountered in various dominant point detection
algorithms. The inherent nature of scale-space filtering in the
procedure is addressed, and the performance of the procedure is
compared to those of several other dominant point detection
algorithms, using a number of examples
Thesaurus computerised pattern recognition; computerised picture processing
; filtering and prediction theory; parallel algorithms
Other Terms dominant point detection; computerised picture processing;
computerised pattern recognition; digital curves; parallel
algorithm; scale factor selection; scale-space filtering
ClassCodes B6140C; C5260B; C1250
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3477406
AbstractNos. B89071040; C89061512
ISSN 01628828
References 27
U.S. Copyright Clearance Center Code
0162-8828/89/0800-0859$01.00
Country Pub. USA
date 1165
------------------------------------------------------------
Author Gould, K.; Shah, M.;
Dept. of Comput. Sci., Central Florida Univ., Orlando, FL, USA
Title The trajectory primal sketch: a multi-scale scheme for
representing motion characteristics
Source Proceedings CVPR '89 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.89CH2752-4); Part: San
Diego, CA, USA; Part: 4-8 June 1989;
Sponsored by: IEEE;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xvii+693;
1989; pp. 79-85
Abstract Conventional approaches to dynamic scene analysis do not use
motion itself explicitly for recognition. The authors propose a
different approach for the use of motion in a computer vision
system which uses the motion characteristics of moving objects
without actually recovering the structure. In this approach, the
extended trajectories followed by the objects are considered. It
is argued that in many cases, where an object has a fixed and
predefined motion, the trajectory of several points may serve to
uniquely identify the object. In this approach, the trajectories
are analyzed at multiple scales to identify important events
corresponding to discontinuities in direction, speed, and
acceleration using scale space. These important events are
recorded in a presentation called trajectory primal sketch.
Experimental results are presented graphically, demonstrating the
potential value of this approach
Thesaurus computer vision; computerised pattern recognition; computerised
picture processing
Other Terms feature extraction; computerised pattern recognition;
trajectory primal sketch; motion characteristics; dynamic scene
analysis; computer vision; multiple scales; scale space
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3471654
AbstractNos. B89063626; C89059532
ISBN or SBN 0 8186 1952 x
References 6
U.S. Copyright Clearance Center Code
CH2752-4/89/0000-0079$01.00
Country Pub. USA
date 1163
------------------------------------------------------------
Author Saund, E.;
Dept. of Brain & Cognitive Sci., MIT, Cambridge, MA, USA
Title Adding scale to the primal sketch
Source Proceedings CVPR '89 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.89CH2752-4); Part: San
Diego, CA, USA; Part: 4-8 June 1989;
Sponsored by: IEEE;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xvii+693;
1989; pp. 70-8
Abstract The author shows how a scale dimension can be added to Marr's
(1976) primal sketch to facilitate construction of multiscale
descriptions of two-dimensional scales. In contrast to
conventional scale-space approaches, this method omits any
smoothing or blurring and performs grouping operations on
symbolic shape tokens residing in a scale-space blackboard data
structure. Two types of grouping operation are introduced: (1)
fine-to-coarse aggregation of primitive-edge tokens builds
coarser-scale edge maps from finer-scale information; and (2)
pairwise grouping of symmetrically placed primitive edges gives
rise to a primitive partial region token denoting curved-contour,
primitive-corner, and bar events. The resulting collection of
tokens makes the fundamental edge and region components of a
shape's geometry available to later symbolic processes, leading
to shape recognition or other tasks
Thesaurus computerised pattern recognition; computerised picture processing
; data structures
Other Terms Marr's primal sketch; 2D scales; feature extraction;
computerised picture processing; pattern recognition; scale
dimension; multiscale descriptions; grouping operations;
symbolic shape tokens; scale-space blackboard data structure;
fine-to-coarse aggregation; primitive-edge tokens; curved-
contour; primitive-corner; bar events; shape recognition
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3471653
AbstractNos. B89063625; C89059531
ISBN or SBN 0 8186 1952 x
References 25
U.S. Copyright Clearance Center Code
CH2752-4/89/0000-0070$01.00
Country Pub. USA
date 1163
------------------------------------------------------------
Author Baker, H.H.;
Artificial Intelligence Center, SRI Int., Menlo Park, CA, USA
Title Building surfaces of evolution: the Weaving Wall
Source International Journal of Computer Vision;
Int. J. Comput. Vis. (Netherlands);
vol.3, no.1;
May 1989; pp. 51-71
Abstract Describes a three-dimensional surface-construction process
designed for the analysis of image sequences. Named the Weaving
Wall, the process operates over images as they arrive from a
sensor, knitting together, along a parallel frontier, connected
descriptions of images as they evolve over time. Although the
Weaving Wall was developed to support a tracking mechanism for
recovering the three-dimensional structure of a scene being
traversed, other applications of the surface-building process
have since become apparent. These include rendering and
computation of tomographic medical data, display of higher-
dimensional analytic functions, edge detection on the scale-space
surface, and display and analysis of material fracture data. More
generally, the Weaving Wall may be of use in representing the
evolution of any two-dimensional imagery varying in a nearly
continuous manner along a third dimension
Thesaurus computer vision; computerised picture processing
Other Terms Weaving Wall; three-dimensional surface-construction process;
image sequences; descriptions of images; tracking mechanism;
three-dimensional structure; surface-building process;
tomographic medical data; edge detection; material fracture data
ClassCodes C5260B
Article Type Theoretical / Mathematical
Coden IJCVEQ
Language English
RecordType Journal
ControlNo. 3467785
AbstractNos. C89061520
ISSN 09205691
References 16
Country Pub. Netherlands
date 1162
------------------------------------------------------------
Author Chen, M.-H.; Yan, P.-F.;
Dept. of Electr. Eng., State Univ. of New York, Stony Brook, NY,
USA
Title A multiscanning approach based on morphological filtering
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.11, no.7;
July 1989; pp. 694-700
Abstract It is argued that the mathematical morphology method seems to be
more reasonable and powerful in studying certain multiscaling
vision problems than the approach that uses derivatives of
Gaussian-shaped filters of different sizes. To show the validity
of this method, the authors concentrated on an application that
involves forming scale-space image of a 2-D shape using
morphological opening filtering. A proof is given to show that
morphological opening filtering has a property of not introducing
additional zero-crossings as one moves to a coarser scale. This
is a different result from the conclusion by A.L. Yuille and T.A.
Poggio (ibid., vol.PAMI-8, Jan. 1986) that the Gaussian filter is
the only filter with this property. In addition, opening
filtering is computationaly simpler than the Gaussian filter
Thesaurus filtering and prediction theory; picture processing
Other Terms picture processing; image analysis; morphological filtering;
multiscaling vision; scale-space image; 2-D shape; opening
filtering
ClassCodes B6140C; C1260; C1250
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3466264
AbstractNos. B89063518; C89059802
ISSN 01628828
References 8
U.S. Copyright Clearance Center Code
0162-8828/89/0700-0694$01.00
Country Pub. USA
date 1164
------------------------------------------------------------
Author Zakharov, S.M.; Manykin, E.A.
Title Optical image transformation by photon-echo signals in dynamic
echo-holography
Source Optika i Spektroskopiya;
Opt. Spektrosk. (USSR);
vol.65, no.2;
Translated in: Optics and Spectroscopy;
Translated in: Opt. Spectrosc. (USA);
Translated in: vol.65, no.2;
Translated in: Aug. 1988; pp. 249-51;
Aug. 1988; pp. 419-23
Abstract Nonstationary optical image transformation by photon-echo signals
is examined for usage of resonant media as dynamic spectral-
selective holograms. The properties of scale space-time
processing achieved in multilevel quantum systems are discussed
Thesaurus holography; photon echo
Other Terms photon-echo signals; dynamic echo-holography; optical image
transformation; dynamic spectral-selective holograms; space-
time processing; multilevel quantum systems
ClassCodes A4240; A4265G; B4350; B4340
Article Type Theoretical / Mathematical
Coden OSFMA3; OPSUA3
Language English
RecordType Journal
ControlNo. 3460120
AbstractNos. A89106787; B89062776
ISSN 00304034
ISSN (Trans) 0030400X
References 18
U.S. Copyright Clearance Center Code
0030-400X/88/080249-03$05.00
Country Pub. USSR
Country Pub. translation
USA
date 1152
------------------------------------------------------------
Author Tsui, H.T.; Chu, K.C.;
Dept. of Electron., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Title 3D object recognition by scale space feature tracking and
subtemplate matching
Source Intelligent Robots and Computer Vision; Part: Cambridge, MA, USA;
Part: 7-11 Nov. 1988;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1002;
1989; pp. 609-16
Abstract A method to recognize 3D objects by detecting features at
multiple scales and subtemplate matching is proposed. Depth map
data of an object is first smoothed by Gaussian filtering at the
coarsest scale and the Gaussian curvature at each point is
computed. Extremal points are determined and an extremal point
region (EPR) associated with each extremal point is defined. A
spherical window which is invariant with rotation in 3-space is
used to extract a surface patch around each extremal point for
subtemplate matching. Processing and subtemplate matching are
repeated at next finer scale to resolve ambiguities
Thesaurus filtering and prediction theory; pattern recognition; picture
processing
Other Terms depth map data; 3D object recognition; picture processing;
pattern recognition; scale space; feature tracking;
subtemplate matching; Gaussian filtering; Gaussian curvature;
extremal point region; spherical window
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3418937
AbstractNos. B89050108; C89045971
ISSN 0277786X
References 17
Country Pub. USA
date 1155
------------------------------------------------------------
Author Rueff, M.;
Fraunhofer Inst. for Manuf. Eng. & Autom., Stuttgart, West Germany
Title Can scale space filtering enhance fractal analysis?
Source Intelligent Robots and Computer Vision; Part: Cambridge, MA, USA;
Part: 7-11 Nov. 1988;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.1002;
1989; pp. 136-43
Abstract Fractal dimensions are quantities which have been shown to be
useful in the classification and segmentation of textures with
scaling behaviour. Problems arising in the numerical
determination of fractal dimensions are briefly mentioned. Scale
space filtering techniques are suggested to overcome some of
these problems which in particular are given with the detection
of the limited scaling regions of natural textures
Thesaurus computerised pattern recognition; computerised picture processing
; filtering and prediction theory; fractals
Other Terms texture segmentation; computerised picture processing;
computerised pattern recognition; scale space filtering;
fractal analysis; scaling behaviour; fractal dimensions
ClassCodes B6140C; C1250; C5260B; C1260; C6130B
Article Type Theoretical / Mathematical
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3418902
AbstractNos. B89050101; C89045950
ISSN 0277786X
References 15
Country Pub. USA
date 1155
------------------------------------------------------------
Author Lu, Y.; Jain, R.C.;
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor,
MI, USA
Title Behavior of edges in scale space
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.11, no.4;
April 1989; pp. 337-56
Abstract An analysis is presented of the behavior of edges in scale space
for deriving rules useful in reasoning. This analysis of liner
edges at different scales in images includes the mutual influence
of edges and identifies at what scale neighboring edges start
influencing the response of a Laplacian or Gaussian operator.
Dislocation of edges, false edges, and merging of edges in the
scale space are examined to formulate rules for reasoning in the
scale space. The theorems, corollaries, and assertions presented
can be used to recover edges, and related features, in complex
images. The results reported include one lemma, three theorems, a
number of corollaries and six assertions. The rigorous
mathematical proofs for the theorems and corollaries are
presented. These theorems and corollaries are further applied to
more general situations, and the results are summarized in six
assertions. A qualitative description as well as some
experimental results are presented for each assertion
Thesaurus artificial intelligence; computerised pattern recognition;
computerised picture processing
Other Terms edge behaviour; edge recovery; picture processing;
computerised pattern recognition; scale space; reasoning;
Laplacian or Gaussian operator; corollaries; assertions;
complex images
ClassCodes B6140C; C1250; C1230
Article Type Theoretical / Mathematical; Experimental
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3401985
AbstractNos. B89044086; C89041490
ISSN 01628828
References 30
U.S. Copyright Clearance Center Code
0162-8828/89/0400-0337$01.00
Country Pub. USA
date 1161
------------------------------------------------------------
Author Piech, M.A.; Piech, K.R.;
State Univ. of New York, Buffalo, NY, USA
Title Hyperspectral interactions: invariance and scaling
Source Applied Optics;
Appl. Opt. (USA);
vol.28, no.3;
1 Feb. 1989; pp. 481-9
Abstract The authors present new invariance and scaling results for scale
space analysis of hyperspectral data. First, they note that a
hyperspectral curve can be segmented into independent regions
selected by features of scale space fingerprints. These
fingerprint features are persistent inflection points that
precisely locate major atmospheric features that define the
regions. The strength and location of hyperspectral features in
one atmospheric region are independent of features in other
regions; as a result, hyperspectral analysis can be simplified to
a region-by-region analysis. The authors then generate simple
scaling and invariance rules for features within such a spectral
region. They show that the scale of individual features is
independent of the details of feature shape and depends only on
the area of the feature. Interacting features in turn exhibit a
fascinating bifurcation behavior: at large separations features
behave independently; at smaller separations features interact
and their scales are damped; below a critical separation distance
(the bifurcation point) the features nest. The scales of features
above the bifurcation point, the scales of the nested features,
and the location of the bifurcation point depend only on the
feature areas and not on shape-associated parameters of the
individual features
Thesaurus atmospheric spectra; remote sensing
Other Terms remote sensing; invariance; scaling; scale space analysis;
hyperspectral data; fingerprint features; inflection points;
major atmospheric features; region-by-region analysis;
bifurcation behavior; nested features; shape-associated
parameters
ClassCodes A9265H; B7730
Article Type Theoretical / Mathematical
Coden APOPAI
Language English
RecordType Journal
ControlNo. 3381244
AbstractNos. A89074019; B89040555
ISSN 00036935
References 15
U.S. Copyright Clearance Center Code
0003-6935/89/030481-09$02.00/0
Country Pub. USA
date 1159
------------------------------------------------------------
Author Chengsan Zhuang;
Dept. of Comput. Sci. & Autom., Chengdu Univ. of Sci. & Technol.,
Sichuan, China
Title Scale-based hierarchical description and matching of waveforms
Source 9th International Conference on Pattern Recognition (IEEE Cat. No.
88CH2614-6); Part: Rome, Italy; Part: 14-17 Nov. 1988;
Sponsored by: Int. Assoc. Pattern Recogition;
Washington, DC, USA;
IEEE Comput. Soc. Press;
2 vol. xxxvi+1299;
1988; pp. 1268-70 vol.2
Abstract An approach for obtaining hierarchical symbolical description of
waveforms is proposed and a method for matching them is also
given. The whole procedure is divided into three steps: first,
scale-space filtering is applied to each waveform; second, peaks
and valleys of all outputs of the filter are extracted; finally,
a probability relaxation labeling algorithm is used to accomplish
the matching. Results of experiments with synthetic data show
that this approach is able to implement the rubberlike matching
and the results obtained are not sensitive to noise
Thesaurus pattern recognition
Other Terms pattern recognition; scale based waveform description;
hierarchical symbolical description; scale-space filtering;
probability relaxation labeling algorithm; rubberlike matching
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3372736
AbstractNos. B89032585; C89030532
ISBN or SBN 0 8186 0878 1
References 8
U.S. Copyright Clearance Center Code
CH2614-6/88/0000-1268$01.00
Country Pub. USA
date 1155
------------------------------------------------------------
Author Ranganathan, N.; Shah, M.;
Dept. of Comput. Sci., Central Florida Univ., Orlando, FL, USA
Title A scale-space chip
Source 9th International Conference on Pattern Recognition (IEEE Cat. No.
88CH2614-6); Part: Rome, Italy; Part: 14-17 Nov. 1988;
Sponsored by: Int. Assoc. Pattern Recogition;
Washington, DC, USA;
IEEE Comput. Soc. Press;
2 vol. xxxvi+1299;
1988; pp. 420-4 vol.1
Abstract Scale-space is a representation for detecting and organising
intensity changes that occur at various scales in an image. A
single-chip VLSI design is proposed for scale-space computation
in one and two dimensions. The architecture of the chip is based
on an algorithm that can provide speeds that are an order of
magnitude higher than the speeds obtainable from the other
systems proposed in the literature. The design uses the
principles of modularity, expandability and parallelism, and
fully utilizes the three properties of the Gaussian: symmetry,
separability, and scaling. The proposed algorithm and the
hardware architecture use a very high degree of pipelining and
parallelism. The chip can be implemented in either nMOS or CMOS
technology
Thesaurus computer vision; computerised pattern recognition; computerised
picture processing; integrated circuit technology;
microprocessor chips; MOS integrated circuits; parallel
architectures; pipeline processing; VLSI
Other Terms computer vision; picture processing; chip architectures; image
intensity change detection; intensity change organisation; nMOS
technology; pattern recognition; scale-space chip; single-chip
VLSI design; modularity; expandability; parallelism; symmetry;
separability; pipelining; CMOS technology
ClassCodes B2570D; B2570F; B1265F; C5260B; C1250; C5220; C5130
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3363224
AbstractNos. B89030597; C89026356
ISBN or SBN 0 8186 0878 1
References 14
U.S. Copyright Clearance Center Code
CH2614-6/88/0000-0420$01.00
Country Pub. USA
date 1155
------------------------------------------------------------
Author Huang Nan; Abbott, M.G.; Beattie, R.J.;
Huazhong Univ. of Sci. & Technol., Wuhan, China
Title Approaches to low level image processing for vision guided seam
tracking systems
Source 9th International Conference on Pattern Recognition (IEEE Cat. No.
88CH2614-6); Part: Rome, Italy; Part: 14-17 Nov. 1988;
Sponsored by: Int. Assoc. Pattern Recogition;
Washington, DC, USA;
IEEE Comput. Soc. Press;
2 vol. xxxvi+1299;
1988; pp. 601-3 vol.1
Abstract Vision systems based on triangulation with active laser light
sources are becoming widely used in robot arc welding. The sensor
and preprocessing hardware provide a one-dimensional signal
representing a cross section of the seam being tracked. This work
describes and compares two different approaches to analyzing
these signals as a precursor to matching them to predefined
templates. One approach uses an expert systems methodology, while
the other uses scale-space filtering
Thesaurus arc welding; computer vision; expert systems; filtering and
prediction theory; industrial robots; position control
Other Terms industrial robots; position control; computer vision; low
level image processing; vision guided seam tracking systems;
triangulation; active laser light sources; robot arc welding;
expert systems; scale-space filtering
ClassCodes C3355F; C3120C; C3390; C5260B; C7410F; C1260
Article Type Practical
Language English
RecordType Conference
ControlNo. 3351295
AbstractNos. C89025352
ISBN or SBN 0 8186 0878 1
References 2
U.S. Copyright Clearance Center Code
CH2614-6/88/0000-0601$01.00
Country Pub. USA
date 1155
------------------------------------------------------------
Author Mokhtarian, F.;
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC,
Canada
Title Evolution properties of space curves
Source Second International Conference on Computer Vision (IEEE Cat. No.
88CH2664-1); Part: Tampa, FL, USA; Part: 5-8 Dec. 1988;
Sponsored by: IEEE;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xiv+708;
1988; pp. 100-5
Abstract Several results are presented on the evolution properties of
space curves which provide theoretical underpinning for the
curvature and torsion scale space representation for space curves.
It is shown that properties such as connectedness and closedness
are preserved during evolution, that the centre of mass does not
move as the curve evolves, that evolution is invariant under
affine transformations of the curve such as uniform scaling,
rotation, and translation, and that a space curve remains inside
its convex hull during evolution. The two main theorems of this
work show that there are strong constraints on the shape of a
space curve in the neighborhood of a cusp point just before and
just after the formation of that point
Thesaurus computational geometry; computer vision; picture processing
Other Terms space curves; curvature; torsion scale space representation;
connectedness; closedness; centre of mass; affine
transformations; uniform scaling; rotation; translation;
convex hull; cusp point
ClassCodes B6140C; B0250; B0290Z; C1250; C5260B; C1160; C4190
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3350339
AbstractNos. B89025150; C89024169
ISBN or SBN 0 8186 0883 8
References 9
U.S. Copyright Clearance Center Code
CH2664-1/88/0000-0100$01.00
Country Pub. USA
date 1156
------------------------------------------------------------
Author Perona, P.; Malik, J.;
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley,
CA, USA
Title A network for multiscale image segmentation
Source 1988 IEEE International Symposium on Circuits and Systems.
Proceedings (Cat. No.88CH2458-8); Part: Espoo, Finland; Part: 7-
9 June 1988;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
3 vol. 2915;
1988; pp. 2565-8 vol.3
Abstract Detecting edges of objects in their images is a basic problem in
computational vision. The authors present the major ideas behind
the use of scale space and anisotropic diffusion for edge
detection, show that anisotropic diffusion can enhance edges,
suggest a network implementation of anisotropic diffusion, and
provide design criteria for obtaining networks performing scale
space and edge detection. The results of a software
implementation are shown
Thesaurus computer vision; computerised pattern recognition; picture
processing
Other Terms picture processing; multiscale image segmentation;
computational vision; scale space; anisotropic diffusion; edge
detection; network implementation; design criteria; software
implementation
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3339973
AbstractNos. B89025186; C89017673
References 12
U.S. Copyright Clearance Center Code
CH2458-8/88/0000-2565$01.00
Country Pub. USA
date 1150
------------------------------------------------------------
Author Gardner, S.;
US Naval Res. Lab., Washington, DC, USA
Title Ultradiffusion, scale space transformation, and the morphology of
neural networks
Source IEEE International Conference on Neural Networks (IEEE Cat. No.
88CH2632-8); Part: San Diego, CA, USA; Part: 24-27 July 1988;
Sponsored by: IEEE;
New York, NY, USA;
IEEE;
2 vol. (699+651);
1988; pp. 617-23 vol.1
Abstract The author proposes the scale-space transformation (SST) as a
paradigm for information processing in biological neural networks.
The SST concept includes scale-space, scale-time, and scale-space-
time mappings. Hierarchical nonlinear (HNL) systems theory,
together with the SST paradigm, causality requirements in the
time domain, and uncertainty constraints in time and space
domains, can be used to develop morphogenic models of biological
neural networks. Since morphogenic models need only capture the
functional modality of their physical counterparts, there may or
may not be an observable resemblance to physical structure. To
illustrate these concepts, the author discusses a morphogenic
model of the mammalian visual system (MVS) in terms of SST
mappings. As an example he uses an exponential retinotopic
mapping, which is called the log Z SST (LZ SST). Using HNL and
SST concepts, the author suggests a layered model of the MVS
neural network
Thesaurus neural nets; nonlinear systems; time-domain analysis
Other Terms hierarchical nonlinear systems; morphology; scale-space
transformation; biological neural networks; scale-space-time
mappings; time domain; morphogenic model; mammalian visual
system
ClassCodes A8730E; A8710; C1290L
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3327891
AbstractNos. A89038193; C89017972
References 20
Country Pub. USA
date 1151
------------------------------------------------------------
Author Caelli, T.M.; Bischof, W.F.; Zhi-Qiang Liu;
Dept. of Psychol., Queens Univ., Kingston, Ont., Canada
Title Filter-based models for pattern classification
Source Pattern Recognition;
Pattern Recognit. (UK);
vol.21, no.6;
1988; pp. 639-50
Abstract Considers a technique for pattern classification based upon the
development of prototypes which capture the distinguishing
features ('disjunctive prototypes') of each pattern class and,
via cross-correlation with incoming test images, enable efficient
pattern classification. The authors evaluate such a
classification procedure with prototypes based on the images per
se (direct code), Gabor scheme (multiple fixed filter
representation) and an edge (scale space-based) coding scheme.
The authors' analyses, the comparisons with human pattern
classification performance, indicate that the edge-only
disjunctive prototypes provide the most discriminating
classification performance and are the more representative of
human behaviour
Thesaurus filtering and prediction theory; pattern recognition
Other Terms pattern recognition; edge coding; pattern classification;
disjunctive prototypes; cross-correlation; test images; Gabor
scheme; edge-only disjunctive prototypes; human behaviour
ClassCodes B6140C; C1250; C1260
Article Type Practical; Theoretical / Mathematical
Coden PTNRA8
Language English
RecordType Journal
ControlNo. 3325466
AbstractNos. B89017974; C89017608
ISSN 00313203
References 13
U.S. Copyright Clearance Center Code
0031-3203/88/$3.00+.00
Country Pub. UK
date 1145
------------------------------------------------------------
Author Clark, J.J.;
Div. of Appl. Sci., Harvard Univ., Cambridge, MA, USA
Title Singularity theory and phantom edges in scale space
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.10, no.5;
Sept. 1988; pp. 720-7
Abstract The process of detecting edges in a one-dimensional signal by
finding the zeros of the second derivative of the signal can be
interpreted as the process of detecting the critical points of a
general class of contrast functions that are applied to the
signal. It is shown that the second derivative of the contrast
function at the critical point is related to the classification
of the associated edge as being phantom or authentic. The
contrast of authentic edges decreases with filter scale, while
the contrast of phantom edges are shown to increase with scale.
As the filter scale increases, an authentic edge must either turn
into a phantom edge or join with a phantom edge and vanish. The
points in the scale space at which these events occur are seen to
be singular points of the contrast function. Using ideas from
singularity, or catastrophy theory, the scale map contours near
these singular points are found to be either vertical or parabolic
Thesaurus catastrophe theory; filtering and prediction theory; pattern
recognition; picture processing; signal processing
Other Terms 1D signal; picture processing; edge detection; pattern
recognition; singularity theory; phantom edges; scale space;
contrast functions; filter scale; catastrophy theory; scale
map contours
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 3310488
AbstractNos. B89017925; C89011043
ISSN 01628828
References 23
U.S. Copyright Clearance Center Code
0162-8828/88/0900-0720$01.00
Country Pub. USA
date 1153
------------------------------------------------------------
Author Sakou, H.; Yoda, H.; Ejiri, M.;
Central Res. Lab., Hitachi Ltd., Tokyo, Japan
Title An algorithm for matching distorted waveforms using a scale-based
description
Source Proceedings of IAPR Workshop on Computer Vision: Special Hardware
and Industrial Applications; Part: Tokyo, Japan; Part: 12-14
Oct. 1988;
Sponsored by: Int. Assoc. Pattern Recognition;
Tokyo, Japan;
Univ. Tokyo;
x+459;
1988; pp. 329-34
Abstract Proposes a matching algorithm for two mutually-distorted
waveforms each having partial differences in the hierarchical
structure of its scale-space. This algorithm is applied to
matching of two-dimensional shapes and to pattern-width
measurement of semiconductor chip patterns obtained from a
scanning electron microscope (SEM)
Thesaurus computerised pattern recognition; integrated circuit technology;
waveform analysis
Other Terms scale-based description; matching algorithm; mutually-distorted
waveforms; partial differences; scale-space; two-dimensional
shapes; pattern-width measurement; semiconductor chip patterns;
scanning electron microscope; SEM
ClassCodes B6140C; B2570; C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3306639
AbstractNos. B89010676; C89011133
References 7
Country Pub. Japan
date 1154
------------------------------------------------------------
Author Bertero, M.; Poggio, T.A.; Torre, V.;
Dept. of Phys., Istituto Nazionale di Fisica Nucl., Genova, Italy
Title Ill-posed problems in early vision
Source Proceedings of the IEEE;
Proc. IEEE (USA);
vol.76, no.8;
Aug. 1988; pp. 869-89
Abstract Mathematical results on ill-posed and ill-conditioned problems
are reviewed and the formal aspects of regularization theory in
the linear case are introduced. Specific topics in early vision
and their regularization are then analyzed rigorously,
characterizing existence, uniqueness, and stability of solutions.
A fundamental difficulty that arises in almost every vision
problem is scale, that is, the resolution at which to operate.
Methods that have been proposed to deal with the problem include
scale-space techniques that consider the behavior of the result
across a continuum of scales. From the point of view of
regulation theory, the concept of scale is related quite directly
to the regularization parameter lambda . It suggested that
methods used to obtained the optimal value of lambda may provide,
either directly or after suitable modification, the optimal scale
associated with the specific instance of certain problems
Thesaurus computer vision
Other Terms first state of processing; computer vision; ill posed conditions
; solution existence; solution uniqueness; early vision; ill-
conditioned problems; regularization theory; analyzed rigorously
; existence; uniqueness; stability of solutions; vision
problem; resolution; scale-space techniques; regulation theory;
concept of scale; regularization parameter; optimal scale
ClassCodes B6140C; C5260B; C1250
Article Type Bibliography/Literature Suvery; Theoretical / Mathematical
Coden IEEPAD
Language English
RecordType Journal
ControlNo. 3302796
AbstractNos. B89010577; C89013324
ISSN 00189219
References 89
U.S. Copyright Clearance Center Code
0018-9219/88/0800-0869$01.00
Country Pub. USA
date 1152
------------------------------------------------------------
Author Nguyen, D.T.; Ding-Yi Xu;
Dept. of Electr. & Electron. Eng., Auckland Univ., New Zealand
Title Scale based algorithm for recognition of blurred planar objects
Source IEE Proceedings E (Computers and Digital Techniques);
IEE Proc. E, Comput. Digit. Tech. (UK);
vol.135, no.6;
Nov. 1988; pp. 307-11
Abstract The paper presents an algorithm based on scale-space analysis,
for the recognition of blurred planar objects. Apart from
satisfying the usual requirements for invariance under
translation, rotation and scaling, the algorithm is also
invariant under blurring, that is, across all levels of detail or
scales. The technique makes use of the spatial coincidence of the
inflexion points on the object contour at all scales, and of the
fact that no new such points are created as the object becomes
more blurred. The algorithm therefore searches for the best match
of these points at a single scale in the scale-space image. The
algorithm was implemented on an IBM/AT in Modula-2 programming
language, and was tested out on a group of 20 geographical maps
of different sizes and at varying distances from the camera. A
recognition rate of 95 to 100% and an average recognition time of
2.5 seconds were obtained by an efficient organisation of the
template dictionary
Thesaurus computerised pattern recognition; computerised picture processing
Other Terms blurred planar objects recognition; scale based algorithm;
scale-space analysis; translation; rotation; scaling; spatial
coincidence; IBM/AT; Modula-2 programming language
ClassCodes B6140C; C5260B; C5530
Article Type Practical
Coden IPETD3
Language English
RecordType Journal
ControlNo. 3300476
AbstractNos. B89010540; C89013300
ISSN 01437062
References 7
U.S. Copyright Clearance Center Code
0143-7062/88/$3.00+0.00
Country Pub. UK
date 1155
------------------------------------------------------------
Author Meer, P.;
Center for Autom. Res., Maryland Univ., College Park, MD, USA
Title Simulation of constant size multiresolution representations on
image pyramids
Source Pattern Recognition Letters;
Pattern Recognit. Lett. (Netherlands);
vol.8, no.4;
Nov. 1988; pp. 229-36
Abstract An image pyramid is a hierarchy of representations of the input
derived by recursive smoothing and decimation. Image pyramids are
built in log(image-size) time with the consecutive levels having
their size and resolution reduced by a constant factor. Similar
structures with the representations decreasing only in resolution
but not in size are also of interest. The author simulates such
constant size multiresolution representations of the input on
image pyramids by increasing the number of values stored in the
cells of the host structure. Constant size representations allow
parallel processing in applications such as scale-space filtering
and multiresolution edge detection
Thesaurus computer vision; parallel processing
Other Terms parallel processing; computer vision; constant size
multiresolution representations; image pyramids; recursive
smoothing; decimation; scale-space filtering; multiresolution
edge detection
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical
Coden PRLEDG
Language English
RecordType Journal
ControlNo. 3299162
AbstractNos. B89010569; C89011077
ISSN 01678655
References 21
U.S. Copyright Clearance Center Code
0167-8655/88/$3.50
Country Pub. Netherlands
date 1155
------------------------------------------------------------
Author Koenderink, J.J.;
Dept. of Eng. Sci., Oxford Univ., UK
Title Scale-time
Source Biological Cybernetics;
Biol. Cybern. (West Germany);
vol.58, no.3;
1988; pp. 159-62
Abstract Scale-space is a valuable tool in image processing and artificial
vision. It is also of interest in the modeling of organic vision
because mammalian visual systems appear to employ 'hardware'
implementations of scale-space. Similar methods are used in the
temporal domain, but such methods so far devised violate temporal
causality. A conceptually simple and logically consistent scale-
time which does not violate temporal causality, yet which
conserves causality in the resolution domain at any given time is
proposed. The filter kernels are not Gaussians (that would
certainly lead to a violation of temporal causality) but are
related to the Gaussians via a simple transformation of the time
axis. They depend on a pair of parameters, one that has the
character of a temporal delay and one that specifies the temporal
resolution. In the limit for long delays (but fixed resolution)
these kernels asymptotically approach the Gaussian again.
Extensions of the theory towards a scale space-time are discussed
Thesaurus computer vision; computerised picture processing; filtering and
prediction theory; vision
Other Terms computer vision; nonGaussian kernels; image processing;
artificial vision; organic vision; mammalian visual systems;
temporal causality; scale-time; resolution domain; filter
kernels; temporal delay; temporal resolution
ClassCodes A8710; A8732E; C1250; C1290L; C5260B; C1260
Article Type Theoretical / Mathematical
Coden BICYAF
Language English
RecordType Journal
ControlNo. 3279914
AbstractNos. A89009821; C89005736
ISSN 03401200
References 10
Country Pub. West Germany
date 1145
------------------------------------------------------------
Author Cooke, M.P.; Green, P.D.;
Dept. of Comput. Sci., Sheffield Univ., UK
Title On finding objects in spectrograms: a multiscale relaxation
labelling approach
Source Recent Advances in Speech Understanding and Dialog Systems.
Proceedings of the NATO Advanced Institute; Part: Bad Windsheim,
West Germany; Part: 5-18 July 1987;
Sponsored by: NATO;
Berlin, West Germany;
Springer-Verlag;
x+521;
1988; pp. 129-33
Editor Niemann, H.; Lang, M.; Sagerer, G.
Abstract Describes a new technique for object finding in spectrograms, and
illustrates the idea with an application to the formant-tracking
task. Starting with a multiscale representation of speech spectra,
a probabilistic relaxation labelling algorithm is applied to
determine primitive interpretations of the spectral components.
Finally, a cross-scale integration procedure enables the scale
space to be collapsed in a principled manner. The techniques are
illustrated with an example of voiced speech
Thesaurus spectral analysis; speech analysis and processing
Other Terms spectrograms; multiscale relaxation labelling approach; object
finding; formant-tracking task; speech spectra; probabilistic
relaxation labelling algorithm; primitive interpretations;
spectral components; cross-scale integration procedure; scale
space; voiced speech
ClassCodes B6130
Article Type Practical
Language English
RecordType Conference
ControlNo. 3278750
AbstractNos. B89003828
ISBN or SBN 3 540 19245 X
References 4
Country Pub. West Germany
date 1138
------------------------------------------------------------
Author Mokhtarian, F.;
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC,
Canada
Title Multi-scale description of space curves and three-dimensional
objects
Source Proceedings CVPR '88: The Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.88CH2605-4); Part: Ann
Arbor, MI, USA; Part: 5-9 June 1988;
Sponsored by: IEEE;
Translated in: B19;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xv+975;
1988; pp. 298-303
Abstract The authors address the problem of representing the shape of
three-dimensional or space curves. This problem is important
since space curves can be used to model the shape of many three
dimensional objects effectively and economically. A number of
shape representation methods that operate on two-dimensional
objects and can be extended to apply to space curves are reviewed
briefly and their shortcomings discussed. Next, the concepts of
curvature and torsion of a space curve are explained. Arc-length
parametrization followed by Gaussian convolution is used to
compute curvature and torsion on a space curve at varying levels
of detail. Information of both the curvature and torsion of the
curve over a continuum of scales are combined to produce the
curvature and torsion scale-space images of the curve. These
images are essentially invariant under rotation, uniform scaling,
and translation of the curve and are used as a representation for
it. The application of this technique to a common three-
dimensional object is demonstrated. The proposed representation
is then evaluated according to several criteria that any shape
representation method should ideally satisfy
Thesaurus computational geometry; pattern recognition
Other Terms pattern recognition; arc-length parameterisation; shape
representation; computational geometry; multiscale description;
space curves; Gaussian
ClassCodes B6140C; B0290Z; C1250; C4190
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3258529
AbstractNos. B88073322; C88060965
ISBN or SBN 0 8186 0862 5
References 32
U.S. Copyright Clearance Center Code
CH2605-4/88/0000-0298$01.00
Country Pub. USA
date 1150
------------------------------------------------------------
Author Teh, C.-H.; Chin, R.T.;
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Title A scale-independent dominant point detection algorithm
Source Proceedings CVPR '88: The Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.88CH2605-4); Part: Ann
Arbor, MI, USA; Part: 5-9 June 1988;
Sponsored by: IEEE;
Translated in: B08;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xv+975;
1988; pp. 229-34
Abstract A parallel algorithm for detecting dominant points on a digital
closed curve is presented. The procedure requires no input
parameter and remains reliable even when features of multiple
sizes are present on the digital curve. The procedure first
determines the region of support for each point based on its
local properties, then computes measures of relative significance
(e.g. curvature) of each point, and finally detects dominant
points by a process of nonmaxima suppression. This procedure
leads to an important observation that the performance of
dominant points detection depends not only on the accuracy of the
measure of significance, but mainly precise determination of the
region of support. This solves the fundamental problem of scale
factor selection encountered in various dominant point detection
algorithms. The inherent nature of scale-space filtering in the
procedure is addressed and the performance of the procedure is
compared to those of several other dominant point-detection
algorithms, using a number of examples
Thesaurus computerised pattern recognition; parallel algorithms
Other Terms computerised pattern recognition; scale-independent dominant
point detection algorithm; scale factor selection
ClassCodes B6140C; C5260B; C1250
Article Type Practical
Language English
RecordType Conference
ControlNo. 3258520
AbstractNos. B88073313; C88063144
ISBN or SBN 0 8186 0862 5
References 13
U.S. Copyright Clearance Center Code
CH2605-4/88/0000-0229$01.00
Country Pub. USA
date 1150
------------------------------------------------------------
Author Glass, J.R.; Zue, V.W.;
Dept. of Electr. Eng. & Comput. Sci., MIT, Cambridge, MA, USA
Title Multi-level acoustic segmentation of continuous speech
Source ICASSP 88: 1988 International Conference on Acoustics, Speech,
and Signal Processing (Cat. No.88CH2561-9); Part: New York, NY,
USA; Part: 11-14 April 1988;
Sponsored by: IEEE;
Translated in: C07;
New York, NY, USA;
IEEE;
5 vol.2928;
1988; pp. 429-32 vol.1
Abstract As part of the goal to better understand the relationship between
the speech signal and the underlying phonemic representation, the
authors have developed a procedure that describes the acoustic
structure of the signal. Acoustic events are embedded in a multi-
level structure in which information ranging from coarse to fine
is represented in an organized fashion. An analysis of the
acoustic structure, using 500 utterances from 100 different
talkers, show that it captures over 96% of the acoustic-phonetic
events of interest with an insertion rate of less than 5%. The
signal representation, and the algorithms for determining the
acoustic segments and the multi-level structure are described.
Performance results and a comparison with scale-space filtering
is also included. Possible use of this segmental description for
automatic speech recognition is discussed
Thesaurus acoustic signal processing; speech analysis and processing;
speech recognition
Other Terms speech analysis; speech processing; multilevel acoustic
segmentation; continuous speech recognition; speech signal;
phonemic representation; acoustic; insertion rate; signal
representation; scale-space filtering; automatic speech
recognition
ClassCodes A4370; A4360; B6130; B6140; C1250C
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 3257059
AbstractNos. A88128461; B88072795; C88061042
References 8
U.S. Copyright Clearance Center Code
CH2561-9/88/0000-0429$1.00
Country Pub. USA
date 1148
------------------------------------------------------------
Author Mackworth, S.K.; Mokhtarian, F.;
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC,
Canada
Title The renormalized curvature scale space and the evolution
properties of planar curves
Source Proceedings CVPR '88: The Computer Society Conference on Computer
Vision and Pattern Recognition (Cat. No.88CH2605-4); Part: Ann
Arbor, MI, USA; Part: 5-9 June 1988;
Sponsored by: IEEE;
Translated in: B22;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xv+975;
1988; pp. 318-26
Abstract The curvature scale-space image of a planar curve is computed by
convolving a path-based parametric representation of the curve
with a Gaussian function of variance sigma /sup 2/, extracting
the zeros of curvature of the convolved curves and combining them
in a scale space representation of the curve. For any given curve
Gamma , the process of generating the ordered sequence of curves
( Gamma /sub sigma / mod sigma >or=0) is the evolution of Gamma .
It is shown that the normalized arc length parameter of a curve
is, in general, not the normalized arch length parameter of a
convolved version of that curve. A novel method of computing the
curvature scale space image reparametrizes each convolved curve
by its normalized arc length parameter. Zeros of curvature are
then expressed in that new parametrization. The result is the
renormalized curvature scale-space image and is more suitable for
matching curves similar in shape. Scaling properties of planar
curves and the curvature scale space image are also investigated.
It is shown that no new curvature zero-crossings are created at
the higher scales of the curvature scale space image of a planar
curve in C/sub 1/ if the curve remains in C/sub 1/ during
evolution. Several results are presented on the preservation of
various properties of planar curves under the evolution process
Thesaurus computational geometry
Other Terms computational geometry; evolution properties; curvature scale-
space image; planar curve; path-based parametric representation;
Gaussian function
ClassCodes C4190
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3248007
AbstractNos. C88062342
ISBN or SBN 0 8186 0862 5
References 10
U.S. Copyright Clearance Center Code
CH2605-4/88/0000-0318$01.00
Country Pub. USA
date 1150
------------------------------------------------------------
Author Ranganathan, N.; Shah, M.;
Dept. of Comp. Sci., Central Florida Univ., Orlando, FL, USA
Title A VLSI architecture for computing scale space
Source Computer Vision, Graphics, and Image Processing;
Comput. Vis. Graph. Image Process. (USA);
vol.43, no.2;
Translated in: A04;
Aug. 1988; pp. 178-204
Abstract Meaningful information about a scene is captured in the intensity
changes in an image. These intensity changes occur at various
scales depending on their physical origins. Scale-space generated
by applying the Laplacian of Gaussian edge detector to the image
at a continuum of scales is a powerful representation for
detecting and organizing these intensity changes symbolically and
has proved to be very useful for one-dimensional signals. The
high computational cost of generating scale-space in two
dimensions has restricted its use in images. This paper proposes
a very efficient single chip VLSI design for scale-space
computation in one and two dimensions. The architecture of the
chip is based on an algorithm that can provide speeds that are of
an order to magnitude higher than the speeds obtainable from
other systems proposed in the literature. The design uses the
principles of modularity, expandability, and parallelism, and
fully utilizes the three properties of Gaussian symmetry,
separability, and scaling. Moreover, the proposed algorithm does
not approximate the Laplacian of the Gaussian operator; it uses
instead four one-dimensional convolutions to obtain the
computations in two dimensions. The proposed architecture has not
been built
Thesaurus computer vision; computerised pattern recognition; computerised
picture processing; microprocessor chips; VLSI
Other Terms computer vision; picture processing; VLSI architecture;
intensity changes; Gaussian edge detector; scale-space
computation; modularity; expandability; parallelism; one-
dimensional convolutions
ClassCodes B2570; C5130; C5260B
Article Type Practical
Coden CVGPDB
Language English
RecordType Journal
ControlNo. 3241831
AbstractNos. B88064637; C88063071
ISSN 0734189X
References 32
U.S. Copyright Clearance Center Code
0734-189X/88/$3.00
Country Pub. USA
date 1152
------------------------------------------------------------
Author Kass, M.; Witkin, A.; Terzopoulos, D.;
Schlumberger Palo Alto Res., CA, USA
Title Snakes: active contour models
Source International Journal of Computer Vision;
Int. J. Comput. Vis. (Netherlands);
vol.1, no.4;
Translated in: A03;
1987; pp. 321-31
Abstract A snake is an energy-minimizing spline guided by external
constraint forces and influenced by image forces that pull it
toward features such as lines and edges. Snakes are active
contour models: they lock onto nearby edges, localizing them
accurately. Scale-space continuation can be used to enlarge the
capture region surrounding a feature. Snakes provide a unified
account of a number of visual problems, including detection of
edges, lines, and subjective contours; motion tracking; and
stereo matching
Thesaurus computer vision
Other Terms scale-space continuation; active contour models; snake; energy-
minimizing spline; external constraint forces; image forces;
lines; edges; capture region; subjective contours; motion
tracking; stereo matching
ClassCodes B6140C; C1250; C5260B
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Journal
ControlNo. 3235173
AbstractNos. B88066638; C88057363
ISSN 09205691
References 25
Country Pub. Netherlands
date 1132
------------------------------------------------------------
Author Piech, M.A.;
Dept. of Math., State Univ. of New York, Buffalo, NY, USA
Title Comments on fingerprints of two-dimensional edge models
Source Computer Vision, Graphics, and Image Processing;
Comput. Vis. Graph. Image Process. (USA);
vol.42, no.3;
Translated in: A07;
June 1988; pp. 381-6
Abstract M. Shah, A. Sood and R. Jain have published an interesting scale-
space analysis of pulse and staircase edge models, both one- and
two-dimensional (see ibid., vol.34, p.321-43, 1986). This note
comments upon Shah, Sood and Jain's analysis of the two-
dimensional step edge, pulse edge and staircase edge models.
Their derivation of the scale-space images and fingerprints can
be simplified by taking advantage of a key geometric feature of
Gaussian filters, namely rotational invariance. The fingerprints
of these three models can easily and directly be deduced
geometrically from the fingerprints of the one-dimensional models.
The fingerprints should be viewed as cylinders over a base curve
which is precisely the fingerprint of the corresponding one-
dimensional edge model. In this way fingerprints of the two-
dimensional models can be immediately visualized from their one-
dimensional counterparts. The authors also demonstrate that the
range of influence of one edge upon another edge located a
distance d away begins at a scale of d/3
Thesaurus filtering and prediction theory; pattern recognition; picture
processing
Other Terms pulse edge models; fingerprints; two-dimensional edge models;
scale-space analysis; staircase edge models; Gaussian filters;
rotational invariance
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden CVGPDB
Language English
RecordType Journal
ControlNo. 3170388
AbstractNos. B88046158; C88037751
ISSN 0734189X
References 2
U.S. Copyright Clearance Center Code
0734-189X/88/$3.00
Country Pub. USA
date 1150
------------------------------------------------------------
Author Fan, T.J.; Medioni, G.; Nevatia, R.;
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles,
CA, USA
Title 3-D surface description using curvature properties
Source Optical and Digital Pattern Recognition; Part: Los Angeles, CA,
USA; Part: 13-15 Jan. 1987;
Sponsored by: SPIE;
Proceedings of the SPIE - The International Society for Optical
Engineering;
vol.754;
Translated in: A15;
1987; pp. 100-6
Abstract Presents a method to extract and represent significant physical
properties of a surface, using curvature properties of this
surface. The authors compute curvature in 4 different directions
and detect extrema and zero-crossings for each of these one
dimensional curves. Since this computation is very noise
sensitive, they filter these features using a scale-space
tracking approach: they smooth the image with Gaussian masks of
increasing variance, detecting features at the smoothest level
and localizing them at the original one. They then partially
group these features into junctions which correspond to
significant physical properties, such as depth discontinuities,
surface discontinuities, smooth extrema, and link them into
curves. They believe that these descriptions capture most of the
information present in the original image, but are more suited to
further processing, such as matching with a model. They then
illustrate this technique with several examples
Thesaurus pattern recognition
Other Terms surface description; curvature properties; extrema; zero-
crossings; scale-space tracking approach; Gaussian masks
ClassCodes B6140C; C1250; C5260B
Article Type Theoretical / Mathematical; Experimental
Coden PSISDG
Language English
RecordType Conference
ControlNo. 3169681
AbstractNos. B88046201; C88037777
ISSN 0277786X
References 25
Country Pub. USA
date 1132
------------------------------------------------------------
Author Bischof, W.F.; Caelli, T.;
Dept. of Psychol., Alberta Univ., Edmonton, Alta., Canada
Title Parsing scale-space and spatial stability analysis
Source Computer Vision, Graphics, and Image Processing;
Comput. Vis. Graph. Image Process. (USA);
vol.42, no.2;
Translated in: A03;
May 1988; pp. 192-205
Abstract The scale-space S(x, sigma ) of a signal I(x) is defined as the
space of the zero-crossings from ( Del /sup 2/G( sigma )*I(x)),
where G is a Gaussian filter. The authors present a new method
for parsing scale-space, spatial stability analysis, that allows
the localization of region boundaries from scale space. Spatial
stability analysis is based on the observation that zero-
crossings of region boundaries remain spatially stable over
changes in filter scale. It is shown that spatial stability
analysis leads to an edge detection scheme with good noise
resilience characteristics and that it can lead to improvements
in 'shape from texture' methods
Thesaurus computerised pattern recognition; computerised signal processing;
filtering and prediction theory
Other Terms computerised pattern recognition; zero-crossings; Gaussian
filter; parsing; spatial stability analysis; scale space;
edge detection; noise resilience
ClassCodes C1250; C1260
Article Type Theoretical / Mathematical
Coden CVGPDB
Language English
RecordType Journal
ControlNo. 3160349
AbstractNos. C88037744
ISSN 0734189X
References 29
U.S. Copyright Clearance Center Code
0734-189X/88/$3.00
Country Pub. USA
date 1149
------------------------------------------------------------
Author Perona, P.; Malik, J.;
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley,
CA, USA
Title Scale space and edge detection using anisotropic diffusion
Source Proceedings of the IEEE Computer Society Workshop on Computer
Vision (Cat. No.87TH0210-5); Part: Miami Beach, FL, USA; Part:
30 Nov.-2 Dec. 1987;
Translated in: A03;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xi+370;
1987; pp. 16-22
Abstract The scale-space technique introduced by A.P. Witkin (1983)
involves generating coarser resolution images by convolving the
original image with a Gaussian kernel, or equivalently by using
the original image as the initial condition of a diffusion
process. This approach has a major drawback; it is difficult to
obtain accurately the locations of the 'semantically meaningful'
edges at coarse scales. The authors suggest a novel definition of
scale-space and introduce a class of algorithms that realize it
using anisotropic diffusion. The diffusion coefficient is chosen
to vary spatially in such a way as to encourage intraregion
smoothing in preference to interregion smoothing. It is shown
that the 'no new maxima should be generated at coarse scales'
property of conventional scale space is preserved. As the region
boundaries in the proposed approach remain sharp, a high quality
edge detector which successfully utilizes global information is
obtained. Experimental results are shown on a couple of images.
The algorithm involves simple, local operations replicated over
the image, making parallel hardware implementation feasible
Thesaurus diffusion; pattern recognition
Other Terms pattern recognition; edge detection; anisotropic diffusion;
scale-space technique; Gaussian kernel; intraregion smoothing;
global information
ClassCodes B0240Z; B6140C; C1140Z; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3118766
AbstractNos. B88028092; C88022065
ISBN or SBN 0 8186 4779 5
References 13
U.S. Copyright Clearance Center Code
TH0210-5/87/0000-0016$01.0
Country Pub. USA
date 1142
------------------------------------------------------------
Author Sato, M.; Wada, T.;
Res. Lab. of Precision Machinery & Electron., Tokyo Inst. of
Technol., Yokohama, Japan
Title A hierarchical representation of generalized waveforms
Source Transactions of the Institute of Electronics, Information and
Communication Engineers D;
Trans. Inst. Electron. Inf. Commun. Eng. D (Japan);
vol.J70D, no.11;
Translated in: A20;
Nov. 1987; pp. 2154-9
Abstract A method to generate a tree is proposed, which represents the
hierarchical structure of waveforms by scale space filtering. The
generated tree called the structure line describes the relation
of the convex and the concave regions of scale space filtered
waveform called the generalized waveform. The structure line is
defined by some derivatives of the generalized waveform, and
holds the same structure as a trinary tree topologically. The
properties of structure line are shown, and also that this method
is effective to represent the waveform hierarchically
Thesaurus computerised pattern recognition; hierarchical systems
Other Terms scale space filtering; hierarchical representation; generalized
waveforms; hierarchical structure of waveforms; scale space
filtering
ClassCodes C1250
Article Type Theoretical / Mathematical
Coden DJTDE2
Language Japanese
RecordType Journal
ControlNo. 3087813
AbstractNos. C88016244
ISSN 0374468X
References 7
Country Pub. Japan
date 1142
------------------------------------------------------------
Author Nguyen, D.T.; Xu, D.-Y.;
Dept. of Electr. & Electron. Eng., Auckland Univ., New Zealand
Title Efficient technique for scale-space imaging of planar objects
Source Electronics Letters;
Electron. Lett. (UK);
vol.23, no.24;
Translated in: C08;
19 Nov. 1987; pp. 1326-7
Abstract The scale-space image, i.e. the plot of the location of the
inflection points against the scale of the Gaussian smoothing
filter, is an effective description for planar object recognition.
Recent techniques of scale-space imaging involve four
convolutions for each scale, while the authors' technique by
smoothing the curvature of the object contour directly requires
only one convolution per scale
Thesaurus computerised picture processing
Other Terms inflection points location; curvature smoothing; scale-space
imaging of planar objects; scale-space image; Gaussian
smoothing filter; planar object recognition; one convolution
per scale
ClassCodes B6140C; C1250; C1260
Article Type Theoretical / Mathematical
Coden ELLEAK
Language English
RecordType Journal
ControlNo. 3070945
AbstractNos. B88014758; C88010536
ISSN 00135194
References 4
U.S. Copyright Clearance Center Code
0013-5194/87/$2.00+0.00
Country Pub. UK
date 1142
------------------------------------------------------------
Author Shimizu, E.; Matsushita, K.; Takahashi, H.
Title Sensors and new signal processing techniques
Source Systems and Control;
Syst. Control (Japan);
vol.31, no.2;
Translated in: T01;
Feb. 1987; pp. 87-94
Abstract Sensors and signal processing techniques have been developed to
meet application requirements. This paper explains new signal
processing techniques in three classifications: orthogonal-
transfer, matrix, and new signal processing techniques. The
orthogonal-transfer techniques include the Fourier transfer, the
sampling Fourier transfer, the fast Fourier transfer, the Adamahl
transfer, and the Fourier descripter. The matrix technique
explanation focuses on the coordinate transfer type computing for
image processing. As the new signal processing technique, the
optical flow, maximum entropy spectrum, and scale space filtering
are introduced
Thesaurus filtering and prediction theory; Fourier transforms; image
sensors; picture processing; signal processing
Other Terms picture processing; signal processing techniques; orthogonal-
transfer; sampling Fourier transfer; fast Fourier transfer;
Adamahl transfer; Fourier descripter; matrix; coordinate
transfer; image processing; optical flow; maximum entropy
spectrum; scale space filtering
ClassCodes A4230V; B0230; B6140; B7230; B7230G; C1130; C1250; C1260
Article Type General or Review; Theoretical / Mathematical
Coden SYCNA9
Language Japanese
RecordType Journal
ControlNo. 3057091
AbstractNos. A88012591; B88008778; C88005650
ISSN 03744507
References 18
Country Pub. Japan
date 1133
------------------------------------------------------------
Author Huttenlocher, D.P.; Ullman, S.;
Artificial Intelligence Lab., MIT, Cambridge, MA, USA
Title Object recognition using alignment
Source Image Understanding Workshop Proceedings; Part: Los Angeles, CA,
USA; Part: 23-25 Feb. 1987;
Sponsored by: Defense Adv. Res. Projects Agency;
Translated in: C01;
Los Altos, CA, USA;
Morgan Kaufmann;
2 vol. vi+1000;
1987; pp. 370-80 vol.1
Abstract The paper presents an approach to recognition whereby an object
is first aligned with an image using a small number of pairs of
model and image features, and then the aligned model is compared
directly against the image. For instance, the position,
orientation, and scale of an object in three-space can be
determined from three pairs of corresponding model and image
features. By using a small fixed number of features to determine
position and orientation, the alignment process avoids
structuring the recognition problem as an exponential search. To
demonstrate the method, some examples of the recognition of flat
rigid objects with arbitrary three-dimensional position,
orientation, and scale, from a single two-dimensional image, are
given. The recognition system chooses features for alignment
using a scale-space segmentation of edge contours. Finally, the
method is extended to the domain of rigid objects in general
Thesaurus pattern recognition
Other Terms object recognition; alignment; position; orientation; scale;
scale-space segmentation; edge contours
ClassCodes C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3049253
AbstractNos. C88005684
ISBN or SBN 0 934613 36 2
References 19
Country Pub. USA
date 1133
------------------------------------------------------------
Author Lenz, R.;
Linkoping Univ., Sweden
Title Rotation-invariant operators and scale-space filtering
Source Pattern Recognition Letters;
Pattern Recognit. Lett. (Netherlands);
vol.6, no.3;
Translated in: A01;
Aug. 1987; pp. 151-4
Abstract Analysis of images at different spatial scales is known to be an
important tool in the processing of images. One of the most
popular procedures in this branch of image processing is based on
the zero-crossings of the Laplacian. The author analyses the
'Laplacian of the Gaussian' approach with the help of rotation-
invariant operators and shows how the original image is related
to the Gaussian (and Laplace-) filtered version
Thesaurus filtering and prediction theory; Laplace transforms; picture
processing
Other Terms picture processing; Gaussian filtering; Laplacian filtering;
scale-space filtering; image processing; rotation-invariant
operators
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden PRLEDG
Language English
RecordType Journal
ControlNo. 3031460
AbstractNos. B88003189; C88000560
ISSN 01678655
References 7
U.S. Copyright Clearance Center Code
0167-8655/87/$3.50
Country Pub. Netherlands
date 1139
------------------------------------------------------------
Author Witkin, A.; Terzopoulos, D.; Kass, M.;
Schlumberger Palo Alto Res., CA, USA
Title Signal matching through scale space
Source International Journal of Computer Vision;
Int. J. Comput. Vis. (Netherlands);
vol.1, no.2;
Translated in: A02;
1987; pp. 133-44
Abstract Given a collection of similar signals that have been deformed
with respect to each other, the general signal-matching problem
is to recover the deformation. The authors formulate the problem
as the minimization of an energy measure that combines a
smoothness term and a similarity term. The minimization reduces
to a dynamic system governed by a set of coupled, first-order,
differential equations. The dynamic system finds an optimal
solution at a coarse scale and then tracks it continuously to a
fine scale. Among the major themes in recent work on visual
signal matching have been the notions of matching as constrained
optimization, of variational surface reconstruction and of coarse-
to-fine matching. The authors' solution captures these in a
precise, succinct and unified form. Results are presented for one-
dimensional signals, a motion sequence and a stereo pair
Thesaurus computer vision; minimisation; pattern recognition; picture
processing
Other Terms energy-measure minimisation; coupled first-order differential
equations; computer vision; scale space; visual signal matching
; constrained optimization; variational surface reconstruction;
coarse-to-fine matching; one-dimensional signals; motion
sequence; stereo pair
ClassCodes C1180; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Journal
ControlNo. 3026029
AbstractNos. C88000553
ISSN 09205691
References 22
Country Pub. Netherlands
date 1132
------------------------------------------------------------
Author Piech, M.A.; Piech, K.R.;
Dept. of Math., State Univ. of New York, Buffalo, NY, USA
Title Symbolic representation of hyperspectral data
Source Applied Optics;
Appl. Opt. (USA);
vol.26, no.18;
Translated in: D09;
15 Sept. 1987; pp. 4018-26
Abstract The authors have developed a symbolic representation of
hyperspectral data using the scale space techniques of Witkin
(1983). They created a scale space image of hyperspectral data
from convolution with Gaussian masks and then a fingerprint that
extracts individual features from the original data. The
fingerprint provides a context that pairs inflection points and
assigns them to a feature, generates a measure of importance for
each feature, and relates features to each other. The
representation is an ordered sequence of triplets containing a
measure of importance related to the area of each feature and the
left and right inflection points of the feature. The description
is compact, quantitative, and hierarchical, describing the
hyperspectral curve by its most important structural features
first, followed by features of lesser importance
Thesaurus remote sensing; spectroscopy
Other Terms symbolic representation; hyperspectral data; scale space
techniques; scale space image; convolution; Gaussian masks
ClassCodes A0650D; A0765
Article Type Practical; Theoretical / Mathematical
Coden APOPAI
Language English
RecordType Journal
ControlNo. 3021291
AbstractNos. A88000353
ISSN 00036935
References 10
U.S. Copyright Clearance Center Code
0003-6935/87/184018-09/$02.00/0
Country Pub. USA
date 1140
------------------------------------------------------------
Author Cyganski, D.; Orr, J.A.; Cott, T.A.; Dodson, R.;
Dept. of Electr. Eng., Worcester Polytech. Inst., MA, USA
Title Implementation of a tensor differential scale space system
Source Proceedings of the Nineteenth Southeastern Symposium on System
Theory (Cat. No.TH0180-0); Part: Clemson, SC, USA; Part: 15-17
March 1987;
Sponsored by: IEEE;
Translated in: A04;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xvii+575;
1987; pp. 18-22
Abstract A variation on the scale-space representation of planar curves is
introduced, using a parameterization and curvature definition
which extends the range of cases for which scale-space methods
are useful. Previously, the scale-space approach to image
registration and identification was unable to deal with images
skewed by a change in angle between object plane and camera line
of sight. The new approach, using tensor curve differentials to
assemble affine invariant measures, eliminates this restriction,
and is applicable to image pairs related by any affine
transformation. Numerical methods are described for the
implementation of such a system, and the robustness of this
implementation for image distortion due to spatial quantization
is illustrated. By using local averaging in the form of least-
squares low-order polynomial fits, derivatives of the first
through third order of sufficient quality for affine scale-space
representation can be obtained
Thesaurus pattern recognition; picture processing; tensors
Other Terms picture processing; pattern recognition; image identification;
skewed images; tensor differential scale space system; image
registration; image distortion; spatial quantization; local
averaging; least-squares low-order polynomial fits; affine
scale-space representation
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 3000815
AbstractNos. B87069373; C87057279
ISBN or SBN 0 8186 0717 3
References 8
U.S. Copyright Clearance Center Code
0094-2898/87/0000-0018$01.00
Country Pub. USA
date 1134
------------------------------------------------------------
Author Meer, P.; Baugher, S.; Rosenfeld, A.;
Center for Autom. Res., Maryland Univ., College Park, MD, USA
Title Segmentation of multiscale curves by chain pyramids
Source Topical Meeting on Machine Vision. Technical Digest Series Vol.12
(papers in summary form only received); Part: Incline Village,
NV, USA; Part: 18-20 March 1987;
Sponsored by: Opt. Soc. America;
Translated in: B20;
Washington, DC, USA;
Opt. Soc. America;
ix+180;
1987; pp. 176-9
Abstract A planar curve may convey information at several levels of detail.
Locating the curve extrema with the best precision, while trivial
for human perception, presents considerable difficulties for
computer vision. Inconsistent local data must first be eliminated
through soothing. The extrema are then found on the smoothed
curve and projected onto the input. Smoothing in the Fourier
domain is convenient but mapping extrema through the different
levels of resolution is difficult. The scale space approach may
overcome some of the difficulties but is computationally
expensive. The authors propose a new method which performs
smoothing in the image domain. The processing is parallel and the
extrema mapping is immediate. The method is a particular case of
a new approach to processing planar curve data
Thesaurus computerised pattern recognition; computerised picture processing
Other Terms computerised picture processing; segmentation; computerised
pattern recognition; multiscale curves; chain pyramids; planar
curve; computer vision; smoothing; image domain; extrema
mapping
ClassCodes C1250; C5260
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2988226
AbstractNos. C87059740
ISBN or SBN 0 936659 47 5
References 6
Country Pub. USA
date 1134
------------------------------------------------------------
Author Huttenlocher, D.P.; Ullman, S.;
Artificial Intelligence Lab., MIT, Cambridge, MA, USA
Title Object recognition using alignment
Source Proceedings of the First International Conference on Computer
Vision (Cat. No.87CH2465-3); Part: London, UK; Part: 8-11 June
1987;
Sponsored by: IEEE; Int. Assoc. Pattern Recognition;
Translated in: A11;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xii+734;
1987; pp. 102-11
Abstract An approach to recognition is presented in which an object is
first aligned with an image using a small number of pairs of
model and image features, and then the aligned model is compared
directly against the image. For instance, the position,
orientation, and scale of an object in three-space can be
determined from three pairs of corresponding model and image
points. By using a small field number of features to determine
position and orientation, the alignment method avoids structuring
the recognition process as an exponential search. To demonstrate
the method, some examples are presented of recognizing flat rigid
objects with arbitrary three-dimensional position, orientation,
and scale, from a single two-dimensional image. The recognition
system chooses features for alignment using a scale-space
segmentation of edge contours, which yields relatively
distinctive feature labels. The method is extended to the domain
of nonflat objects as well
Thesaurus pattern recognition
Other Terms object recognition; computer vision; alignment; image; image
features; position; orientation; arbitrary three-dimensional
position; scale; scale-space segmentation; edge contours
ClassCodes C1250
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2987827
AbstractNos. C87057244
ISBN or SBN 0 8186 0777 7
References 15
U.S. Copyright Clearance Center Code
CH2465-3/87/0000-0102$01.00
Country Pub. USA
date 1137
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Author Mallat, S.G.;
Dept. of Comput. & Inf. Sci., Pennsylvania Univ., Philadelphia,
PA, USA
Title Scale change versus scale space representation
Source Proceedings of the First International Conference on Computer
Vision (Cat. No.87CH2465-3); Part: London, UK; Part: 8-11 June
1987;
Sponsored by: IEEE; Int. Assoc. Pattern Recognition;
Translated in: C25;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xii+734;
1987; pp. 592-6
Abstract It is acknowledged in the computer vision literature that a
multiscale decomposition of images provides a useful
representation for many image processing algorithms. It is shown
that the wavelet theory, recently developed by Y. Meyer (see
Bourbaki seminar, no.662, 1985/6) enables the author to define
precisely the concept of scaling transformation. For a multiscale
analysis of images, he does not want to process the signal at
each scale because the information is redundant. After processing
the signal at a scale s/sub 0/, it is more efficient to analyze
only the additional details which are available at a higher scale
(greater resolution) s/sub 1/. The wavelet theory enables the
author to mathematically define this difference of information,
and it is pointed out that it can be efficiently computed with a
pyramid transform. This leads to a decomposition of the image in
a set of frequency channels with an orientation selectivity which
is called the scale-change representation. This representation is
particularly well adapted to computer vision tasks such as
texture analysis, edge detection and matching algorithms
Thesaurus computer vision; parallel algorithms; pattern recognition;
picture processing
Other Terms multiscale image decomposition; Meyer wavelet theory; redundant
information; parallel algorithm; scale space representation;
computer vision; image processing; scaling transformation;
pyramid transform; scale-change representation; texture analysis
; edge detection; matching
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 2977760
AbstractNos. B87062369; C87051427
ISBN or SBN 0 8186 0777 7
References 5
U.S. Copyright Clearance Center Code
CH2465-3/87/0000-0592$01.00
Country Pub. USA
date 1137
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Author Hummel, R.; Moniot, R.;
New York Univ., NY, USA
Title Solving ill-conditioned problems by minimizing equation error
Source Proceedings of the First International Conference on Computer
Vision (Cat. No.87CH2465-3); Part: London, UK; Part: 8-11 June
1987;
Sponsored by: IEEE; Int. Assoc. Pattern Recognition;
Translated in: C15;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xii+734;
1987; pp. 527-33
Abstract Ill-conditioned problems arise frequently in computer vision
because the image information contains noise and ambiguities such
that the true identity of the scene is not uniquely specified. A
method in numerical analysis is considered for solving 'inverse
problems' when the degraded scene has undergone a sequence of
steps modeled by a known equation. Reconstruction can then be
attempted by finding a solution that minimizes the deviation from
that equation. The method is exemplified by its application to
the deblurring problem. In this problem, deblurring is achieved
by computing a succession of images, each slightly deblurred from
the previous, such that the complete set satisfies the equations
specifying the diffusion process of blurring. The method can be
viewed as an approach to regularization for problems in which a
scale-space parameter can be used to separate the information
extracted from the image
Thesaurus computer vision; error analysis; numerical methods; picture
processing
Other Terms equation error minimisation; degraded images; image
reconstruction; ill-conditioned problems; computer vision;
numerical analysis; inverse problems; deblurring; diffusion
process; blurring; regularization; scale-space parameter
ClassCodes B0290; B0290B; B6140C; C1250; C4100; C4110
Article Type Theoretical / Mathematical; Experimental
Language English
RecordType Conference
ControlNo. 2977753
AbstractNos. B87062362; C87051420
ISBN or SBN 0 8186 0777 7
References 14
U.S. Copyright Clearance Center Code
CH2465-3/87/0000-0527$01.00
Country Pub. USA
date 1137
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Author Clark, J.J.;
Div. of Appl. Sci., Harvard Univ., Cambridge, MA, USA
Title Singularities of contrast functions in scale space
Source Proceedings of the First International Conference on Computer
Vision (Cat. No.87CH2465-3); Part: London, UK; Part: 8-11 June
1987;
Sponsored by: IEEE; Int. Assoc. Pattern Recognition;
Translated in: C08;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xii+734;
1987; pp. 491-5
Abstract The process of detecting edges in a one-dimensional signal by
finding the zeros of the second derivative of the signal can be
interpreted as the process of detecting the critical points of a
general class of contrast functions which are applied to the
signal. It is shown that the concavity of the contrast function
at a critical point is related to the classification of the
associated edge as being phantom or authentic. The contrast of
authentic edges is shown to decrease with filter scale, while the
contrast of phantom edges is shown to increase with scale. It is
shown that as the filter scale increases, an authentic edge must
either turn into a phantom edge or join with a phantom edge and
vanish. The points in the scale space at which these events occur
are seen to be the singular points of the contrast function.
Using ideas from singularity, or catastrophe, theory, one can
show that the form of the scale map contours near these singular
points is restricted to one of two basic types. The analysis of
the behavior of the contrast function near a singularity also
provides a proof of the property that scale map contours cannot
be created as the filter scale increases
Thesaurus catastrophe theory; filtering and prediction theory; pattern
recognition
Other Terms edge detection; contrast function singularities; contrast
function concavity; singularity theory; catastrophe theory;
pattern recognition; scale space; one-dimensional signal;
authentic edges; phantom edges; filter scale; scale map
contours
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2977746
AbstractNos. B87062355; C87051413
ISBN or SBN 0 8186 0777 7
References 17
U.S. Copyright Clearance Center Code
CH2465-3/87/0000-0491$01.00
Country Pub. USA
date 1137
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Author Blostein, D.; Ahuja, N.;
Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
Title Representation and three-dimensional interpretation of image
texture: An integrated approach
Source Proceedings of the First International Conference on Computer
Vision (Cat. No.87CH2465-3); Part: London, UK; Part: 8-11 June
1987;
Sponsored by: IEEE; Int. Assoc. Pattern Recognition;
Translated in: C01;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xii+734;
1987; pp. 444-9
Abstract A perspective view of a slanted textured surface shows systematic
changes in the density, area and aspect-ratio of texture elements.
These apparent changes in texture element properties can be
analyzed to recover information about the physical layout of the
scene. However, in practice it is difficult to identify texture
elements, especially in images in which the texture elements are
partially occluded or are themselves texture at a finer scale. To
solve this problem, it is necessary to integrate the extraction
of texture elements with the recognition of scene layout. A
method for recovering the orientation of textured surfaces, while
simultaneously identifying texture elements, is presented. A
multiscale region detector, based on measurements in a Delta /sup
2/G (Laplacian-of-Gaussian) scale-space, is used to construct a
set of candidate texture elements. True texture elements are
selected from the set of candidate texture elements by finding
the planar surface that best predicts the observed properties of
the candidate texture elements. Results are shown for a variety
of natural textures, including waves, flowers, rocks, clouds and
dirt clods
Thesaurus pattern recognition; picture processing; surface texture
Other Terms image texture representation; partial occlusions; scene layout
recognition; feature extraction; Laplacian-of-Gaussian scale
space; computer vision; three-dimensional interpretation;
perspective view; slanted textured surface; orientation;
multiscale region detector; waves; flowers; rocks; clouds;
dirt clods
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2977740
AbstractNos. B87062349; C87051407
ISBN or SBN 0 8186 0777 7
References 14
U.S. Copyright Clearance Center Code
CH2465-3/87/0000-0444$01.00
Country Pub. USA
date 1137
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Author Aviad, Z.;
Dept. of Comput. Sci., Carnegie-Mellon Univ., Pittsburgh, PA, USA
Title A discrete scale-space representation
Source Proceedings of the First International Conference on Computer
Vision (Cat. No.87CH2465-3); Part: London, UK; Part: 8-11 June
1987;
Sponsored by: IEEE; Int. Assoc. Pattern Recognition;
Translated in: B21;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xii+734;
1987; pp. 417-21
Abstract A discrete alternative to scale-space filtering is presented. The
method provides for fast solutions to problems of spatial
containment, filtering and matching, without using arbitrary
parameters and smoothing of the input. The discrete space-scale
representation is a hierarchical perceptual organization that has
applications in computer vision research. Examples from actual
implementation are provided
Thesaurus computer vision; filtering and prediction theory
Other Terms discrete scale-space representation; scale-space filtering;
spatial containment; matching; arbitrary parameters; smoothing;
hierarchical perceptual organization; computer vision
ClassCodes B6140; C1250
Article Type Practical; Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2977736
AbstractNos. B87062134; C87051402
ISBN or SBN 0 8186 0777 7
References 14
U.S. Copyright Clearance Center Code
CH2465-3/87/0000-0417$01.00
Country Pub. USA
date 1137
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Author Lyon, R.F.;
Schlumberger Palo Alto Res., CA, USA
Title Speech recognition in scale space
Source Proceedings: ICASSP 87. 1987 International Conference on
Acoustics, Speech, and Signal Processing (Cat. No.87CH2396-0); Par
t: Dallas, TX, USA; Part: 6-9 April 1987;
Sponsored by: IEEE;
Translated in: G20;
New York, NY, USA;
IEEE;
4 vol. 2425;
1987; pp. 1265-8 vol.3
Abstract Scale-space filtering, proposed by A.P. Witkin (1984) for
describing natural structure in one-dimensional signals, has been
extended for application to segmentation and description of
vector-valued functions of time, such as speech spectrograms.
Scale-space segmentations of cochleagrams (spectrograms based on
a computational model of the peripheral auditory system) have
been experimentally applied to word recognition. Recognition
using fixed-scale segmentations with finite-state word models and
a Viterbi search has led to speaker-independent digit recognition
accuracies of greater than 97%, about the same as the tests with
nonsegmented cochleagrams
Thesaurus filtering and prediction theory; speech recognition
Other Terms scale space filtering; speech recognition; segmentation;
vector-valued functions of time; speech spectrograms;
cochleagrams; peripheral auditory system; word recognition;
fixed-scale segmentations; finite-state word models; Viterbi
search; speaker-independent digit recognition
ClassCodes B6130; C1250C
Article Type Experimental
Language English
RecordType Conference
ControlNo. 2976912
AbstractNos. B87061729; C87051511
References 6
U.S. Copyright Clearance Center Code
CH2396-0/87/0000-1265$01.00
Country Pub. USA
date 1135
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Author Withgott, M.; Bagley, S.C.; Lyon, R.F.; Bush, M.A.;
Zerox Palo Alto Res. Center, CA, USA
Title Acoustic-phonetic segment classification and scale-space filtering
Source Proceedings: ICASSP 87. 1987 International Conference on
Acoustics, Speech, and Signal Processing (Cat. No.87CH2396-0); Par
t: Dallas, TX, USA; Part: 6-9 April 1987;
Sponsored by: IEEE;
Translated in: E18;
New York, NY, USA;
IEEE;
4 vol. 2425;
1987; pp. 860-3 vol.2
Abstract Scale-space filtering represents one method for automatically
extracting both coarse and fine-grained units from the speech
signal. The authors examine the acoustic-phonetic structure of
segments obtained by scale-space filtering of cochleagrams, and
report on the correspondences between scale-space segments which
are automatically derived and hand-marked acoustic-phonetic
segments. The major advantage of this segmentation is the
flexibility of the data structure
Thesaurus acoustic signal processing; filtering and prediction theory;
speech analysis and processing; speech recognition
Other Terms speech analysis; speech processing; acoustic-phonetic segment
classification; speech recognition; scale-space filtering;
speech signal; cochleagrams; data structure
ClassCodes A4370; B6130; B6140
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2976811
AbstractNos. A87110719; B87061704
References 6
U.S. Copyright Clearance Center Code
CH2396-0/87/0000-0860$01.00
Country Pub. USA
date 1135
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Author Sato, M.; Wada, T.; Kawarada, H.;
Res. Lab. of Precision Machinery & Electron., Tokyo Inst. of
Technol., Yokohama, Japan
Title A hierarchical representation of random waveforms by scale-space
filtering
Source Proceedings: ICASSP 87. 1987 International Conference on
Acoustics, Speech, and Signal Processing (Cat. No.87CH2396-0); Par
t: Dallas, TX, USA; Part: 6-9 April 1987;
Sponsored by: IEEE;
Translated in: B19;
New York, NY, USA;
IEEE;
4 vol. 2425;
1987; pp. 273-6 vol.1
Abstract The authors introduce an analytic line, named the structure line,
on the surface of generalized waveform f(x, sigma ). The
structure line describes the relation of the convex and concave
region of a generalized waveform. The structure line is defined
by some derivatives of the generalized waveform, and has the same
topological structure as a trinary tree. The properties of the
structure line are discussed and some examples are shown. It is
confirmed that the structure line is effective in representing
waveforms hierarchically
Thesaurus filtering and prediction theory; waveform analysis
Other Terms convex region; hierarchical representation; random waveforms;
scale-space filtering; analytic line; structure line; concave
region; derivatives; trinary tree
ClassCodes B0220; B6140
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2976666
AbstractNos. B87061938
References 9
U.S. Copyright Clearance Center Code
CH2396-0/87/0000-0273$01.00
Country Pub. USA
date 1135
------------------------------------------------------------
Author Kass, M.; Witkin, A.; Terzopoulos, D.;
Schlumberger Palo Alto Res., CA, USA
Title Snakes: active contour models
Source Proceedings of the First International Conference on Computer
Vision (Cat. No.87CH2465-3); Part: London, UK; Part: 8-11 June
1987;
Sponsored by: IEEE; Int. Assoc. Pattern Recognition;
Translated in: B03;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xii+734;
1987; pp. 259-68
Abstract A snake is an energy-minimizing spline guided by external
constraint forces and influenced by image forces that pull it
toward features such as lines and edges. Snakes are active
contour models; they lock into nearby edges, localizing them
accurately. Scale-space continuation can be used to enlarge the
capture region surrounding a feature. Snakes provide a unified
account of a number of visual problems, including detection of
edges, lines, and subjective contours, motion tracking, and
stereo matching. The authors have used snakes successfully for
interactive interpretation, in which user-imposed constraint
forces guide the snake near features of interest
Thesaurus computer vision; pattern recognition
Other Terms active contour models; snake; energy-minimizing spline;
external constraint forces; image forces; lines; edges;
capture region; detection of edges; motion tracking; stereo
matching; interactive interpretation
ClassCodes C1250
Article Type Practical; Experimental
Language English
RecordType Conference
ControlNo. 2967219
AbstractNos. C87051386
ISBN or SBN 0 8186 0777 7
References 20
U.S. Copyright Clearance Center Code
CH2465-3/87/0000-0259$01.00
Country Pub. USA
date 1137
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Author Johansen, P.; Skelboe, S.; Grue, K.; Andersen, J.D.;
Dept. of Datalogy, Copenhagen Univ., Denmark
Title Representing signals by their top-points in scale space
Source Eighth International Conference on Pattern Recognition.
Proceedings (Cat. No.86CH2342-4); Part: Paris, France; Part: 27-
31 Oct. 1986;
Sponsored by: IEEE; Int. Assoc. Pattern Recognition;
Translated in: B25;
Washington, DC, USA;
IEEE Comput. Soc. Press;
xxxvi+1300;
1986; pp. 215-17
Abstract In 1983, A. Witkin introduced the fingerprint of a function as a
set F of points in scale space, where scale space is the plane.
Fingerprints are calculated by convolving the function with a
Gaussian filter with continuously varying standard deviation.
Within defined the top-points of the signal as points in scale
space where F has a horizontal tangent. It is proved that
periodic, bandlimited functions are defined up to a
multiplicative constant by their top-points, if this concept is
properly generalized. The uniqueness theorem may be regarded as a
sampling theorem for signals in the scale space
Thesaurus filtering and prediction theory; signal processing
Other Terms signal representation; signal processing; scale space; top-
points; multiplicative constant; sampling theorem
ClassCodes B6140; C1260
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2933821
AbstractNos. B87047850; C87037981
ISBN or SBN 0 8186 0742 4
References 16
U.S. Copyright Clearance Center Code
CH2342-4/86/0000-0215$01.00
Country Pub. USA
date 1128
------------------------------------------------------------
Author Witkin, A.; Terzopoulos, D.; Kass, M.;
Schlumberger Palo Alto Res., CA, USA
Title Signal matching through scale space
Source Proceedings AAAI-86: Fifth National Conference on Artificial
Intelligence; Part: Philadelphia, PA, USA; Part: 11-15 Aug. 1986
;
Sponsored by: American Assoc. Artificial Intelligence; Univ.
Pennsylvania;
Translated in: F13;
Menlo Park, CA, USA;
American Assoc. Artificial Intelligence;
2 vol. xxxii+1165;
1986; pp. 714-19 vol.1;
Available from: Morgan Kaufmann Publishers Inc., Los Altos, CA,
USA
Abstract Given a collection of similar signals that have been deformed
with respect to each other, the general signal matching problem
is to recover the deformation. The authors formulate the problem
as the minimization of an energy measure that combines a
smoothness term and a similarity term. The minimization reduces
to a dynamic system governed by a set of coupled, first-order
differential equations. The dynamic system finds an optimal
solution at a coarse scale and then tracks it continuously to a
fine scale. Among the major themes in recent work on visual
signal matching have been the notions of matching as constrained
optimization, of variational surface reconstruction, and of
coarse-to-fine matching. The solution captures these in a precise,
succinct, and unified form. Results are presented for one-
dimensional signals, a motion sequence, and a stereo pair
Thesaurus picture processing; signal processing
Other Terms image processing; scale space; signal matching; visual
ClassCodes C1250
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2920186
AbstractNos. C87037546
ISBN or SBN 0 934613 13 3
References 17
Country Pub. USA
date 1126
------------------------------------------------------------
Author Carlotto, M.J.;
Anal. Sci. Corp., Reading, MA, USA
Title Histogram analysis using a scale-space approach
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.PAMI-9, no.1;
Translated in: A10;
Jan. 1987; pp. 121-9
Abstract A new application of scale-space filtering to the classical
problem of estimating the parameters of a normal mixture
distribution is described. The technique involves generating a
multiscale description of a histogram by convolving it with a
series of Gaussians of gradually increasing width (standard
deviation), and marking the location and direction of the sign
change of zero-crossings in the second derivative. The resulting
description, or fingerprint, is interpreted by relating pairs of
zero-crossings to modes in the histogram where each mode or
component is modeled by a normal distribution. Zero-crossings
provide information from which estimates of the mixture
parameters are computed. These initial estimates are subsequently
refined, using a iterative maximum likelihood estimation
technique. Varying the scale or resolution of the analysis allows
the number of components used in approximating the histograms to
be controlled
Thesaurus filtering and prediction theory; parameter estimation; picture
processing
Other Terms histogram analysis; parameter estimation; picture processing;
scale-space filtering; normal mixture distribution; zero-
crossings; fingerprint
ClassCodes B6140C; C1220; C1250
Article Type Practical; Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 2901022
AbstractNos. B87039898; C87031838
ISSN 01628828
References 14
U.S. Copyright Clearance Center Code
0162-8828/87/0100-0121$01.00
Country Pub. USA
date 1132
------------------------------------------------------------
Author Blake, A.; Zisserman, A.; Papoulias, A.V.;
Dept. of Comput. Sci., Edinburgh, UK
Title Weak continuity constraints generate uniform scale-space
descriptions of plane curves
Source ECAI '86. 7th European Conference on Artificial Intelligence.
Proceedings; Part: Brighton, UK; Part: 21-25 July 1986;
Translated in: C01;
London, UK;
Conference Services;
2 vol. (597+xxxii+187);
1986; pp. 518-28 vol.1
Abstract Scale-space filtering is a recently developed technique, both
powerful and general, for segmentation and analysis of signals.
Asada and Brady (1984) have amply demonstrated the value of scale-
space for description of curved contours from digitised images.
Weak continuity constraints furnish novel, powerful, nonlinear
filters, to use in place of gaussians, for scale-space filtering.
This has some striking advantages. First, scale-space is uniform,
so that tracking across scale is a trivial task. Structure need
not be preserved to indefinitely fine scale; this leads to an
enrichment of the concept of scale-a rounded corner, for example,
can be represented as a discontinuity at coarse scale but smooth
at fine scale. And, finally, boundary conditions at ends of
curves are handled satisfactorily-it is as easy to analyse open
curves as closed ones
Thesaurus boundary-value problems; computational geometry; computerised
pattern recognition; curve fitting; dynamic programming;
filtering and prediction theory
Other Terms weak continuity constraints; signal analysis; signal
segmentation; nonpreserved structure; plane curves; digitised
images; nonlinear filters; scale-space filtering; boundary
conditions
ClassCodes C1180; C1250; C1260; C4130
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2832019
AbstractNos. C87014666
References 17
Country Pub. UK
date 1125
------------------------------------------------------------
Author Goshtasby, A.; Mokhtarian, F.; Mackworth, A.;
Dept. of Comput. Sci., Kentucky Univ., Lexington, KY, USA
Title Comments on 'Scale-based description and recognition of planar
curves and two-dimensional shapes' (with reply)
Source IEEE Transactions on Pattern Analysis and Machine Intelligence;
IEEE Trans. Pattern Anal. Mach. Intell. (USA);
vol.PAMI-8, no.5;
Translated in: A09;
Sept. 1986; pp. 674-5
Abstract The commenter argues that in the above paper (ibid., vol.PAMI-8,
p., 34-43, Jan. 1986), which describes a technique for
registration of a Landsat image with a map, if the scale of
details in the map and the Landsat image are different, scale-
space images of contours in the map and scale-space images of
region boundaries in the image will not match reliably. The
authors of the paper rebut the commenter's argument
Thesaurus computerised pattern recognition; computerised picture processing
; remote sensing
Other Terms scale based description; pattern recognition; scale based
recognition; 2D shapes; picture processing; image processing;
pattern recognition; planar curves; Landsat image; scale-space
images
ClassCodes B6140C; C1250
Article Type Theoretical / Mathematical
Coden ITPIDJ
Language English
RecordType Journal
ControlNo. 2800963
AbstractNos. B87007830; C87005113
ISSN 01628828
References 2
U.S. Copyright Clearance Center Code
0162-8828/86/0900-0674$01.00
Country Pub. USA
date 1127
------------------------------------------------------------
Author Hummel, R.A.;
Courant Inst. of Math. Sci., New York Univ., NY, USA
Title Representations based on zero-crossings in scale-space
Source Proceedings CVPR '86: IEEE Computer Society Conference on
Computer Vision and Pattern Recognition (Cat. No.86CH2290-5); Part
: Miami Beach, FL, USA; Part: 22-26 June 1986;
Sponsored by: IEEE;
Translated in: B05;
Washington, DC, USA;
IEEE Comput. Soc. Press;
viii+676;
1986; pp. 204-9
Abstract Using the heat equation to formulate the notion of scale-space
filtering, the author shows that the evolution property of level-
crossings in scale-space is equivalent to the maximum principle.
He briefly discusses filtering over bounded domains. He then
considers the completeness of the representation of data by zero-
crossings, and observes that for polynomial data, the issue is
solved by standard results in algebraic geometry. For more
general data, it is argued that gradient information along the
zero-crossings is needed, and that although such information more
than suffices, the representation is still not stable. The author
gives a simple linear procedure for reconstruction of data from
zero-crossings and gradient data along zero-crossings in both
continuous and discrete scale-space domains
Thesaurus filtering and prediction theory; maximum principle; polynomials;
signal processing
Other Terms zero-crossings; heat equation; scale-space filtering;
evolution property; maximum principle; bounded domains;
completeness; polynomial data; algebraic geometry; linear
procedure; gradient data; discrete scale-space domains
ClassCodes B0290F; B6140; C1260; C4130
Article Type Theoretical / Mathematical
Language English
RecordType Conference
ControlNo. 2790139
AbstractNos. B87002549; C87000689
ISBN or SBN 0 8186 0721 1
References 20
U.S. Copyright Clearance Center Code
CH2290-5/86/0000-0204$01.00
Country Pub. USA
date 1124
------------------------------------------------------------
Author Richards, W.; Dawson, B.; Whittington, D.;
Natural Computation Group, MIT, Cambridge, MA, USA
Title Encoding contour shape by curvature extrema
Source Journal of the Optical Society of America A (Optics and Image
Science);
J. Opt. Soc. Am. A, Opt. Image Sci. (USA);
vol.3, no.9;
Translated in: B03;
Sept. 1986; pp. 1483-91
Abstract Curvature extrema provide significant information about the shape
of an image contour, such as a silhouette, and are the basis for
the Hoffman-Richards codon representation for shape. This
representation based on curvature easily translates into a binary
string that will describe the abstract shape of any smooth image
curve. The computation of the basic shape primitives requires
dealing with two even-pervasive problems: contour noise and scale.
The authors show how contour noise can be estimated given
knowledge of the shape of the filter used to compute curvature
from the edge list of the contour. To handle the scale problem,
the authors use an adaptation of Witkin's scale space. The
authors algorithm differs from Witkin's by using a notion of
parts to set criteria for significant structures
Thesaurus computer vision; encoding
Other Terms computer vision; machine vision; shape representation; encoding
; curvature extrema; image contour; silhouette; Hoffman-
Richards codon representation; basic shape primitives; contour
noise
ClassCodes B6120B; B6140C; C1250
Article Type Theoretical / Mathematical
Coden JOAOD6
Language English
RecordType Journal
ControlNo. 2784401
AbstractNos. B87002576; C87000503
ISSN 07403232
References 32
U.S. Copyright Clearance Center Code
0740-3232/86/091483-09$02.00
Country Pub. USA
date 1127