Dot image matching using local affine transformation

The author describes an iterative technique for gradually deforming a mask dot image with successive local affine transformation (LAT) operations so as to yield the best match to an nput dot image. The method uses local structure in the sense that the LAT of a dot at one location is optimized using locations of other dots by means of least-squares data fitting with Gaussian window functions. A multiscale or coarse-fine strategy has been implemented in the algorithm by decreasing the effective interacting neighborhood with each iteration. This technique successfully extracted distortions or displacements from dot images of handwritten figures and random-dot stereograms