GRASP and path relinking hybridizations for the point matching-based image registration problem

Abstract

In the last decade, image registration has proven to be a very active research area when tackling computer vision problems, especially in medical applications. In general, image registration methods aim to find a transformation between two images taken under different conditions. Point matching is an image registration approach based on searching for the right pairing of points between the two images, which involves a combinatorial optimization problem. From this matching, the registration transformation can be inferred by means of numerical methods. In this paper, we tackle the medical image registration problem by means of a recent hybrid metaheuristic composed of two well-known optimization methods: GRASP and path relinking. Several designs based on this new hybrid approach have been tested. Our experimentation with real-world problems shows the combination of GRASP and evolutionary path relinking performs well when compared to previous state-of-the-art image registration approaches adopting both the point matching and transformation parameter approaches.