I know it's a long shot but does anyone have any pointers to generic algorithms - or, even better, Python code - for comparing images and computing a value for the "difference" between them?
What I want to do is to compare two bitmap images (taken from a webcam, so I'll likely be using PIL) and get some idea of the "difference" between them so I can tell if something in the image has changed, eg, a person has entered the field of view. I've had a look at the PIL documentation and all it really told me was how little I knew about image processing :-) and I couldn't see any recipes in the Python Cookbook that are aimed at this problem area. In a perfect world I'd love a method such as CompareImage(Img1, Img2) which would give a result of 255 if they're identical and 0 if not one pixel matches with a sliding scale inbetween but I know I'm probably asking for a lot there... Some ideas I've had is, maybe, increasing the contrast on both images (to take out variation in lighting etc), then compressing the results to get a hash value and comparing the hash, but that sounds likely to produce a lot of false positives. I note that PIL provides a histogram function for counting pixel colour values which sounds potentially useful and if no-one's got any better ideas I'll probably start working in that direction. Or, maybe, dump the bitmap data into a numpy array and do some kind of FFT on that but that feels very CPU- intensive. Those are my ideas so far but I thought it would be worth asking here first in case there are some known-good algorithms for doing this kind of thing rather than me trying to re-invent a wheel that ends up triangular... Thanks! Matthew. -- http://mail.python.org/mailman/listinfo/python-list
