A Quantum-Inspired Genetic Algorithm for Multi-source Affine Image Registration
In this paper we propose a new algorithm for image registration which is a key stage in almost every computer vision system. The algorithm is inspired from both genetic algorithms and quantum computing fields and uses the mutual information as a measure of similarity. The proposed approach is based on some concepts and principles of quantum computing such as quantum bit and states superposition. So, the definitions of the basic genetic operations have been adapted to use the new concepts. The evaluation of each solution is performed by the computation of mutual information between the reference image and the resulting image. The process aims to maximize this mutual information in order to get the best affine transformation parameters which allow the alignment of the two images.
KeywordsGenetic Algorithm Mutual Information Image Registration Quantum Algorithm Artificial Immune System
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- 1.Meshoul, S., Batouche, M., Belhadj-moustefa, K.: An evolutionary framework for image data fusion based on the maximization of mutual information. In: Proceeding of the International Symposium on Software and Systems (I3S 2001) (February 2001)Google Scholar
- 2.Han, K., Kim, J.: Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. IEEE transactions on evolutionary computation 6(6) (December 2002)Google Scholar
- 3.Rieffel, E., Polak, W.: An introduction to quantum computing for non-physicists. arxive.org, quant-ph/9809016 v2 (January 2000) Google Scholar
- 4.Talbi, H., Draa, A., Batouche, M.: A quantum genetic algorithm for image registration. In: Proceeding of the 14th International Conference on Computer Theory and Applications (ICTTA 2004), April 2004, IEEE Press, Los Alamitos (2004) ISBN: 0-7803-8482-2/04Google Scholar