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