Newsgroups: sci.image.processing,comp.graphics.algorithms
Path: cantaloupe.srv.cs.cmu.edu!nntp.club.cc.cmu.edu!miner.usbm.gov!rsg1.er.usgs.gov!stc06.CTD.ORNL.GOV!cs.utk.edu!gatech!howland.reston.ans.net!torn!news.bc.net!newsserver.sfu.ca!fornax!manderso
From: manderso@cs.sfu.ca (Mark Anderson)
Subject: Re: Connected components routines for greyscale iamges?
Message-ID: <519*manderso@cs.sfu.ca>
Reply-To: manderso@cs.sfu.ca (Mark Anderson)
Organization: SFU/TRIUMF Medical Computing Laboratory
References: <3hauk1$r5l@mozo.cc.purdue.edu>
Date: Fri, 10 Feb 1995 01:34:49 GMT
X-Url: http://fas.sfu.ca/1/cs/people/GradStudents/manderso
Lines: 12
Xref: glinda.oz.cs.cmu.edu sci.image.processing:12558 comp.graphics.algorithms:13090

jonesbr@cartoon.ecn.purdue.edu (Brian R. Jones) writes:
>From what I understand, a "connected components" routine will allow the
>program to distinguish "obects" within the image.

Is that the same as a binary connectivity analysis on an image?  First
collect run-lengths of (say) nonzero pixels in each line.  Then collect
these into objects or blobs by looking directly above each run-length
to see if there one in the previous line, if so they are included in
the same object. Is this the kind of thing you're looking for? (I don't
have source code, I just wanted to understand what you're trying to do)
-- 
mark
