I have a picture that I elaborate with my program to obtain a list of coordinates.
There is a matrix represented in the image.
In an ideal test I would get only the sixteen central points of each square of the matrix.
But in actual tests I have some noise points.
I want to use an algorithm to extrapolate from the list of the coordinates the group formed by 16 coordinates that best represent a matrix.
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Example of found points:
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Example of desired result:
How to do this?
Note: The matrix in the image can be rotated a little too, so a rotation-independent algorithm would be great.
Best Answer
Now I'm using an algorithm that worked very well for me.
This is the pseudo code: