Eliminating false matches in image registration through geometric histograms from reflected correspondence vectors

We propose a method to deal with false matches that occur in almost every iteration of iterative closest point (ICP) based registration algorithms. First, a set of correspondences between the two images to be registered are established using the standard ICP criterion. From this set of correspondences, the algorithm as described in Liu et al. (2000) is employed to estimate the essential point defined by geometric properties of reflected correspondence vectors. After a rigid motion, the essential point must be equidistant from reflected correspondences and thus, relative differences between motion equations can be computed and geometric histograms are then constructed at each step of the iteration. False matches are eliminated by only selecting correspondences that show a small relative difference between the two sides of the motion equation. A number of experiments based on both synthetic data and real images demonstrate that the proposed method is accurate, robust, and efficient for the registration of free-form shapes with large motions