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

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 J. Santamaría ( ) Department of Computer Science, EPS de Linares, University of Jaén, C/ Alfonso X El Sabio, 28, 23700 Linares, Jaén, Spain e-mail: [email protected] O. Cordón · S. Damas European Centre for Soft Computing, Edif. Científico-Tecnológico, C/ Gonzalo Gutiérrez Quirós, 33600 Mieres, Asturias, Spain O. Cordón Department of Computer Science and Artificial Intelligence, E.T.S.I. Informática y Telecomunicación, University of Granada, C. Periodista Daniel Saucedo Aranda, s.n., 18071, Granada, Spain R. Martí Department of Statistics and Operations Research, Facultad de Matemáticas, University of Valencia, C/ Dr. Moliner 50, 46100 Burjassot, Valencia, Spain R.J. Palma Department of Computer Science and Artificial Intelligence, ETSIIT, University of Granada, C/ Daniel Saucedo Aranda, 18071 Granada, Spain 170 J. Santamaría et al. 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.