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

Authors:
José Santamaría;Oscar Cordón;Sergio Damas;Rafael Martí;Ricardo J. Palma
Affiliations:
Department of Computer Science, EPS de Linares, University of Jaén, Jaén, Spain 23700;European Centre for Soft Computing, Edif. Científico-Tecnológico, Mieres, Spain 33600 and Department of Computer Science and Artificial Intelligence, E.T.S.I. Informática y Telecomu ...;European Centre for Soft Computing, Edif. Científico-Tecnológico, Mieres, Spain 33600;Department of Statistics and Operations Research, Facultad de Matemáticas, University of Valencia, Burjassot, Spain 46100;Department of Computer Science and Artificial Intelligence, ETSIIT, University of Granada, Granada, Spain 18071
Venue:
Journal of Heuristics
Year:
2012

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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.