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Vision-List Digest	Mon Oct  3 14:01:56 PDT 1988

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Today's Topics:

  Circle Detection Literature
  RE: TEMPORAL DOMAIN IN VISION


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Date:       Fri, 30 Sep 88 15:31:06-0000
From: "x.cao" <eecao%PYR.SWAN.AC.UK@cunyvm.cuny.edu>
Subject: Circle Detection Literature

I am looking for information on image processing  algorithms
and architectures especially suited to detection of circles
in 2D digital images. In particular I am interested in parallel
systems and real-time operation.

I would be most grateful if you could send me details of any references
you have found useful in this area.


                        - - - - - - - - - - - - - - - - - - - -
Cao Xing,              | UUCP  : ...!ukc!pyr.swan.ac.uk!eecao   |
Image Processing Laboratory,     | JANET : eecao@uk.ac.swan.pyr              |
Electrical Engineering Dept.,    | voice : +44 792 205678 Ext. 4698       |
University of Wales,          | Fax     : +44 792 295532                 |
Swansea, SA2 8PP, U.K.         | Telex : 48358                          |
                     - - - - - - - - - - - - - - - - - - - -

[ Related to this is the detection and grouping of general
  curves in imagery. Please post references directly to this List. 
			phil...				]


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Date:     Fri, 30 Sep 88 10:22 EDT
From: Richard A. Young (YOUNG@GMR.COM)
Subject:  RE: TEMPORAL DOMAIN IN VISION
Re:   temporal domain in vision

I take issue with two replies recently made to dmocsny@uceng.UC.EDU (daniel 
mocsny) regarding the Science News article on the work of B. Richmond of NIMH 
and L. Optican of the National Eye Institute on their multiplex filter model 
for encoding data on neural spike trains: 

L. Adrian Griffis (lag@cseg.uucp):
> I'm not an expert in this field, but this suggests to me that many of the 
> special tricks that neurons of the eye employ may be attempts to overcome 
> space limitations rather than to make other processing schemes possible.  

James Wilbur Lewis ( jwl@ernie.Berkeley.EDU):
> Another disturbing loose end was the lack of discussion about how this
> information might be propagated across synapses...It's an interesting result, 
> but I think they may have jumped the gun with the conclusion they drew.

Instead, I have a more positive view of Richmond and Optican's work after 
reviewing their publications (see references at end), and talking with them 
at the recent Neural Net meetings in Boston. I am impressed with their 
approach and research. I think that the issue of temporal coding deserves 
much more careful attention by vision and neural net researchers than it has 
received over the years.  Richmond and Optican have produced the first hard 
published evidence I am aware of in the primate visual system that temporal 
codes can carry meaningful information about visual form.

Their first set of papers dealt with the inferotemporal cortex, a high level 
vision area (Richmond et al., 1987; Richmond and Optican, 1987; Optican and 
Richmond, 1987). They developed a new technique using principal component 
analysis of the neural spike density waveform that allowed them to analyze 
the information content in the temporal patterns in a quantifiable manner. 
Each waveform is expressed in terms of a few coefficients -- the weights on
the principal components. By looking at these weights or "scores", it is 
much easier to see what aspects of the stimulus might be associated with 
the temporal properties of the waveform than has been previously possible.  
They used a set of 64 orthogonal stimulus patterns (Walsh functions), that were 
each presented in a 400 msec flash to awake fixating monkeys. Each stimulus was
shown in two contrast-reversed forms, for a total of 128 stimuli. They devised 
an information theoretic measure which showed that "the amount of information 
transmitted in the temporal modulation of the response was at least twice that 
transmitted by the spike count" alone, which they say is a conservative 
estimate.  In other words, they could predict which stimuli were present to 
a much better extent when the full temporal form of the response was 
considered rather than just the total spike count recorded during a trial. 
Their laboratory has since extended these experiments to the visual cortex 
(Gawne et al., 1987) and the lateral geniculate nucleus (McClurkin et al.) 
and found similar evidence for temporal coding of form.
 
The concept of temporal coding in vision has been around a long time (Troland, 
1921), but primarily in the area of color vision. Unfortunately the prevailing 
bias in biological vision has been against temporal coding in general for 
many years.  It has been difficult to obtain funding or even get articles 
published on the subject.  Richmond and Optican deserve much credit for 
pursuing their research and publishing their data in the face of such strong 
bias (as does Science News for reporting it). The conventional view is that 
all neural information is spatially coded. Such models are variants of the 
"doctrine of specific nerve energies" first postulated by Mueller in the 
nineteenth century. This "labelled-line" hypothesis assumes that the 
particular line activated carries the information. From an engineering 
viewpoint, temporal coding allows for more information to be carried along any 
single line. Such coding allows more efficient use of the limited space 
available in the brain for axons compared to cell bodies (most of the brain 
volume is white matter, not grey!). In terms of biological plausibility, it 
seems to me that the burden of proof should be on those who maintain that such 
codes would NOT be used by the brain.

Anyone who has recorded post-stimulus time histograms from neurons observes
the large variations in the temporal pattern of the responses that occur 
with different stimuli. The "accepted view" is that such variations do 
not encode stimulus characteristics but represent epi-phenomena or noise. Hence
such patterns are typically ignored by researchers. Perhaps one difficulty 
has been that there has not been a good technique to quantify the many 
waveshape patterns that have been observed. It is indeed horrendously difficult
to try to sort the patterns out by eye -- particularly without knowing what the 
significant features might be, if any. With the application of the principal 
component technique to the pattern analysis question, Richmond and Optican 
have made a significant advance, I believe -- it is now possible to quantify
such waveforms and relate their properties to the stimulus in a simple manner.

The question raised by Lewis of whether the nervous system can actually make 
use of such codes is a potentially rich area for research. Chung, Raymond, and
Lettvin (1970) have shown that branching at axonal nodes is an effective
mechanism for decoding temporal messages. Young (1977) was the first to show
that bypassing the receptors and inserting temporal codes directly into 
a human nervous system could led to visual perceptions that were the same for 
a given code across different observers.

Work on temporal coding has potentially revolutionary implications for 
both physiological and neural net research. As was noted at the INNS 
neural net meeting in Boston, temporal coding has not yet been applied or 
even studied by neural net researchers. Neural nets today  can obviously 
change their connection strengths -- but the temporal pattern of the signal on 
the connecting lines is not used to represent or transmit information.  If it 
were, temporal coding methods would seem to offer potentially rich rewards for 
increasing information processing capabilities in neural nets without having to 
increase the number of neurons or their interconnections.

References
-----------
Chung, S. H., Raymond, S. & Lettvin, J. Y. (1970) Multiple meaning in single
visual units. Brain Behav. Evol. 3, 72-101.

Gawne, T. J. , Richmond, B. J., & Optican, L. M. (1987)  Striate cortex neurons 
do not confound pattern, duration, and luminance, Abstr., Soc. for Neuroscience

McClurkin, J.W., Gawne, Richmond, B.J., Optican, L. M., & Robinson, D. L.(1988)
Lateral geniculate nucleus neurons in awake behaving primates: I. Response to 
B&W 2-D patterns, Abstract, Society for Neuroscience.
 
Optican, L. M., & Richmond, B. J. (1987) Temporal encoding of two-dimensional 
patterns by single units in primate inferior temporal cortex. III. Information 
theoretic analysis. J. Neurophysiol., 57, 147-161.
 
Richmond, B. J., Optican, L. M., Podell, M., & Spitzer, H. (1987) Temporal 
encoding of two-dimensional patterns by single units in primate inferior 
temporal cortex. I. Response characteristics. J. Neurophysiol., 57, 132-146.

Richmond, B.J., & Optican, L. M. (1987)  Temporal encoding of two-dimensional 
patterns by single units in primate inferior temporal cortex. II. 
Quantification of response waveform. J. Neurophysiol., 57, 147-161.

Richmond, B. J., Optican, L. M., & Gawne, T. J. (accepted) Neurons use multiple 
messages encoded in temporally modulated spike trains to represent pictures. 
Seeing, Contour, and Colour, ed. J. Kulikowski, Pergamon Press.

Richmond, B. J., Optican, L. M., & Gawne, T. J. (1987) Evidence of an intrinsic 
code for pictures in striate cortex neurons, Abstr., Soc. for Neuroscience.
 
Troland, L. T. (1921) The enigma of color vision. Am. J. Physiol. Op. 2, 23-48.
 
Young, R. A. (1977) Some observations on temporal coding of color vision: 
Psychophysical results. Vision Research, 17, 957-965.


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