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Method of image segmentation based on Fuzzy C-Means Clustering Algorithm and Artificial Fish Swarm Algorithm

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4 Author(s)
Chu XiaoLi ; Guilin Univ. of Electron. Technol., Guilin, China ; Zhu Ying ; Shi JunTao ; Song JiQing

By analyzing advantages and disadvantages of Fuzzy C-Means Clustering Algorithm, a method of image segmentation based on Fuzzy C-Means Clustering Algorithm and Artificial Fish Swarm Algorithm is proposed. The image is segmented in terms of the values of the membership of pixels, Artificial Fish Swarm Algorithm is introduced into Fuzzy C-Means Clustering Algorithm, and through the behavior of prey, follow, swarm of artificial fish, the optimised clustering center could be selected adaptively, then the values of the membership of pixels available with Fuzzy C-Means Clustering Algorithm, and the image segmentation is completed. The experimental results show the effectiveness and feasibility.

Published in:

Intelligent Computing and Integrated Systems (ICISS), 2010 International Conference on

Date of Conference:

22-24 Oct. 2010

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