Abstract: This paper uses PSO algorithm of a powerful global search capabilities to optimize Fuzzy C-Means clustering（FCM） clustering centers，so effectively avoid the traditional FCM sensitive to initial values，data on noise sensitive，vulnerable to the shortcomings of local optimization.The effect of image segmentation has been improved，the performance of the FCM than translation means more stable.Experimental results show that the method is effective.

摘要： 根据粒子群优化算法（PSO）强大的全局搜索能力，提出了用PSO算法优化模糊C均值聚类（FCM）的聚类中心的方法，有效地避免了传统的FCM对初始值及噪声数据敏感，容易陷入局部最优的缺点，同时图像分割的效果也得到了提高，性能也比传统的FCM方法更加稳定。实验结果反映了该方法的有效性。