Tim created another superb solution. The highlights are an elegant center of square's determination using ndgrid. The crux of his method is a convolution for each square not using "same" with an interesting centroid kernel. The comparison between all square convolutions for all rotations utilizes a concise norm metric function. The method should work on non-binary images. The best six matches from the 180x180 upper triangle error array are handily converted into the output format. Thank You Tim for this elegant solution.
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GJam 2012 Qualifier: Tongues
Image Processing 004: Zernike Coefficients
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