I took a few minutes to examine a couple (as in exactly two) multi-frame GIF images from stock spams I received in the past couple days. I'd like a cheap test to decide which frame is the best candidate for OCR without OCRing every frame. The computational costs are high enough already. I have two images, bogus-0.gif and bogus-1.gif (both attached to this message). For each one I ran the following loop: >>> img = Image.open("bogus-0.gif") >>> for (i, frame) in enumerate(ImageSequence(img)): ... bg = max(frame.histogram()) ... npixels = len([x for x in frame.histogram() if x]) ... print bg, npixels For bogus-0.gif I got: 220259 33 217760 52 213225 96 182636 256 222500 1 For bogus-1.gif I got: 326518 5 322180 9 322817 7 280174 11 314741 10 It seems that the frame with the fewest white pixels (or the fewest pixels in the most frequently used palette position) is a decent indicator of the frame with the most useful pixels. I also tried this more expensive test at the shell: % for f in bogus-1-?.png ; do echo "*** $f ***" pngtopnm $f | ocrad | wc -c done *** bogus-1-0.png *** 8 *** bogus-1-1.png *** 31 *** bogus-1-2.png *** 18 *** bogus-1-3.png *** 1219 *** bogus-1-4.png *** 340 The fourth frame does indeed have the most text. This didn't work for the bogus-0.png file because this save loop in Python didn't work properly: >>> img = Image.open("bogus-0.gif") >>> for (i, frame) in enumerate(ImageSequence(img)): ... frame.save(open("bogus-0-%d.png" % i, "wb")) The first frame saved has the proper palette. The other saved frames are just black-and-white. (Can someone with more PIL experience explain why this is so and how to get around it?) I can imagine a spammer putting together a palette where there are 248 not-quite-white palette entries making up an essentially white background and a few entries devoted to displaying text. I'm sure PIL has something we could use to quantize the palette down to 16 colors or so, then use that palette to compute histograms, so I'm not all that worried about that scheme. The spammers do seem to be adapting very quickly (take a look at the frames in bogus-1.gif to see what I mean). I find it hard to believe it's in response to what we're doing here. I'm sure some other much bigger groups must be doing OCR analysis of image-based spam these days. BTW, don't worry too much if your mail program won't display the two images properly. XEmacs didn't like them at all, but Mozilla displayed them just fine. Skip