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)
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Rigid, affine and locally affine registration of free-form surfaces
International Journal of Computer Vision
The 3D marching lines algorithm
Graphical Models and Image Processing
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
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
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
Computers and Operations Research
Feature-based image registration by means of the CHC evolutionary algorithm
Image and Vision Computing
Real-time tabu search for video tracking association
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
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This contribution is devoted to the application of iterated local search to image registration, a very complex, real-world problem in the field of image processing. To do so, we first re-define this parameter estimation problem as a combinatorial optimization problem, then analyze the use of image-specific information to guide the search in the form of an heuristic function, and finally propose its solution by iterated local search.Our algorithm is tested by comparing its performance to that of two different baseline algorithms: iterative closest point, a well-known, image registration technique, a hybrid algorithm including the latter technique within a simulated annealing approach, a multi-start local search procedure, that allows us to check the influence of the search scheme considered in the problem solving, and a real coded genetic algorithm. Four different problem instances are tackled in the experimental study, resulting from two images and two transformations applied on them. Three parameter settings are analyzed in our approach in order to check three heuristic information scenarios where the heuristic is not used at all, is partially used or almost completely guides the search process, as well as two different number of iterations in the algorithms outer-inner loops.