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.
Arrange Vector in descending order
2 b | ~ 2 b
Spectral Distance - Speed Scoring
subtract central cross
Rubik's Cube: 30 Moves or Less: Minimum Avg Time
Skyscrapers - Puzzle
Cubic Integer Constrained Solution
Criss_Cross_000 : Unique elements in a Square array
Slitherlink I: Trivial
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