DocumentCode :
3428699
Title :
Method of image segmentation based on Fuzzy C-Means Clustering Algorithm and Artificial Fish Swarm Algorithm
Author :
Chu, Xiaoli ; Zhu, Ying ; Shi, Jun Tao ; Song, JiQing
Author_Institution :
Guilin Univ. of Electron. Technol., Guilin, China
fYear :
2010
fDate :
22-24 Oct. 2010
Firstpage :
254
Lastpage :
257
Abstract :
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.
Keywords :
fuzzy reasoning; image segmentation; optimisation; pattern clustering; artificial fish swarm algorithm; fuzzy c-means clustering algorithm; image pixels; image segmentation; Image segmentation; Optimization; Pixel; Artificial Fish Swarm Algorithm (AFSA); Fuzzy C-Means Clustering Algorithm(FCM)); Image Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Integrated Systems (ICISS), 2010 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-6834-8
Type :
conf
DOI :
10.1109/ICISS.2010.5657199
Filename :
5657199
Link To Document :
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