关键词: 模糊C-均值聚类, 彩色图像分割, 聚类中心, 微粒群优化算法, 鲁棒性

Abstract: Fuzzy C-means（FCM） clustering algorithm has been widely used in image segmentation.Because of the heavy computing burden of the Fuzzy C-Means clustering and the disadvantage that clustering performance is affected by initial centers of FCM.This paper proposes a method of Fuzzy C-means Clustering based on Particle Swarm Optimization algorithm for image segmentation.As the search is based on density of the cluster center，the computational load is small，thus，the computing speed of FCM can be improved.Experimental results show that this method can make a marked improvement in the speed of fuzzy clustering and can segment the image quickly and effectively．

Key words: fuzzy c-means cluster, color image segmentation, clustering center, particle swarm optimization algorithm, robust