I am currently trying to stitch 4 photographs of a document together. I am using OpenCV 2.9, SURF extractor and descriptor with an hessian threshold of 2000 (otherwise there are too many keypoints). I am rejecting any matches with a distance greater than (2*min_dist) and merge the images using findHomography() (RANSAC method) and warpPerspective().
This is how good it gets at the moment. https://i.stack.imgur.com/aVWWu.jpg
How come the transformation matrix findHomography() is calculating does not seem to be accurate? The matches look fairly good to me: https://i.stack.imgur.com/F8ZNc.jpg
Any ideas how to improve the result? Any preprocessing like binarization, denoising, autocontrasting etc. pp. had no impact at all or made it even worse.