StackOverflow2013

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A few fairly simple things to try that might help: <ul> <li>I would look in detail at what your thresholding is doing, and whether that's really what you want to do. I don't know what graythresh does exactly, but it's possible it's lumping different features that you would want to distinguish into the same pixel values. Have you tried plotting the differences between images without thresholding? Or you could threshold into multiple classes, rather than just black and white.</li> <li>If noise is the main problem, you could try smoothing the images before taking the difference, so that differences in noise would be evened out but differences in large features, caused by motion, would still be there.</li> <li>You could try edge-detecting your images before taking the difference.</li> </ul> As a previous answerer mentioned, you could also look into motion-tracking and registration algorithms, which would estimate the actual motion between each image, rather than just telling you whether the images are different or not. I think this is a decent summary on Wikipedia: <a href="http://en.wikipedia.org/wiki/Video_tracking" rel="nofollow">http://en.wikipedia.org/wiki/Video_tracking</a>. But they can be rather complicated. I think if all you need is to find the time and period of contractions, though, then you wouldn't necessarily need to do a detailed motion tracking or deformable registration between images. All you need to know is when they change significantly. (The "strength" of a contraction is another matter, to define that rigorously you probably would need to know the actual motion going on.)
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1. POMatlab video processing of heart beating. code supplemented
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