Classification: UNCLASSIFIED Caveats: NONE I thought you might be interested in the following: Image Change Detection Algorithms: A Systematic Survey www.ecse.rpi.edu/~roysam/PDF/J51.pdf ====================== "Near set theory provides methods that can be used to extract resemblance information from objects contained in disjoint sets, i.e., it provides a formal basis for the observation, comparison, and classification of objects. The discovery of near sets begins with choosing the appropriate method to describe observed objects. For example, collections of digital images viewed as disjoint sets of points provide a rich hunting ground for near sets." <...> "The Near set Evaluation and Recognition (NEAR) system, is a system developed to demonstrate practical applications of near set theory to the problems of image segmentation evaluation and image correspondence. It was motivated by a need for a freely available software tool that can provide results for research and to generate interest in near set theory" http://en.wikipedia.org/wiki/Near_sets ======= Some phrase I googled searched: Near Sets Psychophysics Color difference Lab color space Salient features Change detection Segmentation image processing Some website you might what to look at www.visionbib.com ieexplore.ieee.org (IEEE digital library) portal.acm.org (ACM digital library) -----Original Message----- From: Classification, clustering, and phylogeny estimation [mailto:[log in to unmask]] On Behalf Of Yakir Gagnon Sent: Friday, May 14, 2010 11:35 AM To: [log in to unmask] Subject: A good measure of distance for pixel intensities Hi! Background: I want to compare two images that are identical in many respects (pixel-wise) but are different in the pixel intensity values they have. I'm aware of the many image comparison methods out there, but I want to keep it very very simple (for all the image analysists: these two images are artificial and made through the same process with some differences without any spatial translation). What I am doing right now: is calculating the euclidian distance between the pixel intensities of the 2 images. The mean of all the distances (if the image is 500*500 pixels then there are 500^2 distances) gives me a measure of how similar those images are. My question is: is the euclidian distance really the best option when comparing natural numbers that can only range between 0 and 255, or should I use some other measure of distance or transform the pixel intensities first? Thanks in advance! Yakir L. Gagnon, PhD student The Lund Vision Group Tel +46 (046) 222 93 40 Cell +46 (073) 753 63 54 Fax +46 (046) 222 44 25 http://www.lu.se/o.o.i.s/7758 <blockedhttp://www.lu.se/o.o.i.s/7758> http://www.google.com/profiles/12.yakir <blockedhttp://www.google.com/profiles/12.yakir> ---------------------------------------------- CLASS-L list. Instructions: http://www.classification-society.org/csna/lists.html#class-l <blockedhttp://www.classification-society.org/csna/lists.html#class-l> Classification: UNCLASSIFIED Caveats: NONE ---------------------------------------------- CLASS-L list. Instructions: http://www.classification-society.org/csna/lists.html#class-l