16 year Chinese learner here (not that it's relevant). I would try to hack a solution via the following approach. 1. Determine the area (if any) near the botto

16 year Chinese learner here (not that it's relevant). I would try to hack a solution via the following approach. 1. Determine the area (if any) near the bottom with black-or-whiteness zones of a constant height (these are likely to be subtitles) by randomly selecting 10 frames from the middle of the movie. Extra points if you have it detect the sub color. 2. For each frame with unique subs, isolate the zones vertically (handles multi-line subs). 3. Determine black-or-whiteness of each vertical column in the text area. Moving inward from the left or right edge, crop everything until the black-or-whiteness within the constant height drops below a certain threshold. In the example shown, this would deal with ′…′二′′′'′ and would look like 0,0,0.01,0,0,0.01,3 4. Crop viciously within the assumed vertical height. This should remove issues like 逯 which should be 这. 5. There is probably a clustering-based approach you can use to remove background noise, either spatially or temporally, eg. temporally via imagemagick[0]: compare frame1.jpg frame2.jpg -compose src -fuzz 10% -highlight-color white -lowlight-color black output.jpg ... alternatively, if there is a surrounding color such as in the example, you could remove any pixel-groups that don't have it. 6. In terms of detecting frames in which you have a new set of subs, just compare the last black-white-extraction of the central maybe-has-subs area (ie. most commonly used portion thereof) with a delta of the last one, remembering no subs is also an option. In many cases this may align with keyframes. If you like to solve image processing problems we're hiring - http://8-food.com/ http://8-food.com/ - email in profile. [0] http://www.imagemagick.org/Usage/compare/#difference http://www.imagemagick.org/Usage/compare/#difference