Robust point correspondence for image registration using optimization with extremal dynamics

Abstract

Robust Point Correspondence for image registration is still a challenging problem in computer vision and many of its related applications. It is a computationally intensive task which requires an expensive search process especially when issues of noisy and outlying data have to be considered. In this paper, we cast the problem as a combinatorial optimization task and we solve it using extremal optimization, a new general purpose heuristic recently proposed by Boettcher and colleagues. We show how this heuristic has been tailored to the point correspondence problem and resulted in an efficient outlier removal scheme. Experimental results are very encouraging and demonstrate the ability of the proposed method in identifying outliers and achieving robust matching. © Springer-Verlag Berlin Heidelberg 2002.