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    <p>Good question.</p> <p>One approach is to represent contours as 2d point clouds and then do registration. More <a href="http://www.cs.cmu.edu/~ytsin/KCReg/" rel="nofollow">simple and clear code in Matlab</a> that can give you affine transform.</p> <p>And <a href="http://code.google.com/p/gmmreg/" rel="nofollow">more complex C++ code(using VXL lib)</a> with python and matlab wrapper included. Or you can use some modificated ICP(iterative closest point) algorithm that is robust to noise and can handle affine transform. </p> <p>Also your contours seems to be not very accurate so it can be a problem.</p> <p>Another approach is to use some kind of registration that use pixel values. <a href="http://www.mathworks.com/matlabcentral/fileexchange/34510-image-registration-gui" rel="nofollow">Matlab code</a> (I think it's using some kind of minimizer+ crosscorrelation metric) Also maybe there is some kind of optical flow registration(or some other kind) that is used in medical imaging.</p> <p>Also you can use point features as SIFT(SURF).</p> <p>You can try it quick in <a href="http://fiji.sc/Fiji" rel="nofollow">FIJI(ImageJ)</a> also this <a href="http://fiji.sc/Landmark_Correspondences" rel="nofollow">link</a>.</p> <ol> <li>Open 2 images</li> <li>Plugins->feature extraction-> sift (or other)</li> <li>Set expected transformation to affine</li> <li>Look at estimated transformation model [3,3] homography matrix in ImageJ log. If it works good then you can implement it in python using OpenCV or maybe using Jython with ImageJ.</li> </ol> <p>And it will be better if you post original images and describe all conditions (it seems that image is changing between frames)</p>
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    1. POAffine transformation between contours in OpenCV
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    1. COI did post the original images. The images are indeed changing because the seafloor conditions change in time. That's why I want to use the black region, which should not be changing, to register the images.
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      1. USRich Signell
 

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