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Published in:
2013 | OriginalPaper | Chapter
101. Image Feature Selection Based on Genetic Algorithm
Authors : Liang Lei, Jun Peng, Bo Yang
Published in: Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012
Publisher: Springer London
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Abstract
Image feature selection is formulated as an optimization problem. When traditional genetic algorithm is used for selecting image feature, it may bring problems of local convergence or precocious puberty because of using a fixed probability of crossover operator and mutation operator. First, the paper gave a brief introduction to image feature selection regarding the purposes, tasks, and commonly used algorithms. Then, the paper improved genetic operator of genetic algorithm, and parallel computing was used to genetic algorithm, to enhance the performance of image feature selection. Finally, experiments show that the improved genetic algorithm is convergent and effective, and applied to image feature selection is successful.