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.
Spot the rectangle
USC Fall 2012 ACM: Rover Maze
Non-zero bits in 10^n.
Knots Contest: Score (ContestSuite)
USC Fall 2012 ACM Question A : Read Input File
ICFP2021 Hole-In-Wall: Figure Validation with Segment Crossing and Segment on Wall Checks
Slitherlink V: Assert/Evolve/Check (large)
USC Fall 2012 ACM : Code Word Minimum Flipped Bits
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