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Detect Chessboard on Images/Scans from Books and Newspapers


I want to write a program which takes a scan or photo taken from books/newspaper and detects a chessboard (like this) on it and gives a image of the chessboard (with parallel edges) as output. My idea was to detect the corners of the chessboard an then generate from this the output chessboard.

So i trained a Haar Classifier for each of the corners. For that i wrote a program in Qt to generate positive Images of the Corner (mark the corner on a image, program generates small image with corner in the middle of the image).

Now i have around 120 Images like this for each corner. I also have ~200 Negative Samples consisting of Images of Books with only printed Text, some with small images and some are just the inside of a chessboard without Corners and Edges.

So i trained the Classifier and tested the performance. About the half of the objects were found. But there where around 80.000 false positive.

I know 120/200 Samples are not much but i wanted to know if i am on the right track and the false positives will go away with more positive/negative samples. Or is there another, better way to detect the Corners of the chessboard.