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Re: Tracking Rectangles with Perspective Distortion
It intentionally doesn't use high level shape detection so that it is more accessible.
The rectangularity score is based on area/bounding rectangle.
The aspect ratio is based on the width and height of the bounding rect, and to make it a bit more robust to distortion, it also uses something called the equivalent rectangle.
The equivalent rectangle uses the area of the particle and the perimeter of the particle and solves for 2X+2Y=perimeter and X*Y=area.
The hollowness counts the pixels that are on for each vertical column of pixels and again for each horizontal row of pixels and compares those counts to thresholds that expect a strong outer band and weak inner band.
Each of these is scaled so that 100 is a good score and lower is not as good. The initial cutoffs are just based on some initial images and are very easy to change.
Can you think of other simple geometric measures that the code could score on the targets?
Greg McKaskle
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