Abstract
In this paper, a novel chaos particle swarm optimization(PSO) clustering algorithm for texture image segmentation was proposed. By means of stochastic property and ergodicity of chaos search mechanism, chaos PSO algorithm can effectively avoid getting into the local convergence. The proposed method combined chaos PSO algorithm with nearest neighbor clustering theorem, which can enhance the efficiency and precision of clustering. And the proposed chaos PSO clustering algorithm was applied to texture image segmentation with gray level co-occurrence matrix. The experimental results indicate that the proposed method can get better segmentation results than PSO algorithm and effectively improve the segmentation precision of texture image.
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Yu, J. (2012). A Novel Chaos PSO Clustering Algorithm for Texture Image Segmentation. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25792-6_41
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DOI: https://doi.org/10.1007/978-3-642-25792-6_41
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