We consider the problem of planar shape registration on binary images. Our primary goal is to investigate novel methodologies which work without feature point extraction and established correspondences; avoid the solution of complex optimization problems; and provide an exact solution regardless of the strength of the distortion. The newly developed techniques are validated on medical images.

A novel solution for reassembling a broken object from its parts without established correspondences, where each part is subject to a linear deformation.

We consider the problem of estimation the parameters of transformations aligning two binary images. The advantage of our algorithm is that it is easy to implement, less sensitive to the strength of the deformation, and robust against segmentation errors.

Sample implementation and benchmark dataset of a nonlinear registration algorithm for recovering planar homographies between 2D shapes.

Sample implementation and benchmark dataset of a correspondence-free binary image registration algorithm.