image matching algorithms

Yu-Xi Lim yuxi at
Tue Mar 11 00:48:21 CET 2008

Daniel Fetchinson wrote:
> Thanks for the info! SIFT really looks like a heavy weight solution,
> but do you think the whole  concept can be simplified if all I needed
> was: given a photo, find similar ones? I mean SIFT first detects
> objects on the image and find similarities, but I don't need the
> detection part at all, all I care about is similarity for the whole
> photo. I surely don't understand the big picture fully but just have
> the general feeling that SIFT and other expert tools are an overkill
> for me and a simplified version would be just as good with a much more
> easily comprehensible core algorithm.

Please describe the kind of photos you are dealing with. Are they 
identical photos, in say different formats or with different metadata? 
Or are they rescaled images? Or maybe they are the same photo cropped 

SIFT will work in more or less the process you described in your first 
post. It basically calculates the N sets of numbers for each image, 
representing the unique features of that image and their relative 
positions. The rest of the process if up to you. You have to compare the 
different sets of numbers to find the image with the minimal difference, 
as opposed to comparing the whole image.

More information about the Python-list mailing list