A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A survey of image registration techniques
ACM Computing Surveys (CSUR)
Rigid, affine and locally affine registration of free-form surfaces
International Journal of Computer Vision
An Experimental Evaluation of a Scatter Search for the Linear Ordering Problem
Journal of Global Optimization
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Scatter Search: Methodology and Implementations in C
Scatter Search: Methodology and Implementations in C
Object Representation and Comparison Inferred from Its Medial Axis
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
A CHC evolutionary algorithm for 3d image registration
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
An approach to multimodal biomedical image registration utilizing particle swarm optimization
IEEE Transactions on Evolutionary Computation
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Image registration is a very active research area in computer vision, namely it is used 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. From this matching, the registration transformation we are searching, can be inferred by means of numerical methods. In this paper, we propose a scatter search (SS) algorithm to solve the matching problem. SS is a hybrid metaheuristic with a good trade-off between search space diversification and intensification. On the one hand, diversity is basically introduced from a population-based approach where systematic combinations of subsets of solutions are performed. On the other hand, intensification is achieved with a local search procedure, to ensure the local improvement of promising solutions. Our computational experimentation in a real-world inter-subject medical registration environment establishes the effectiveness of our procedure in relation to different approaches usually applied to solve the problem.