Fuzzy C-means clustering algorithm for image segmentation based on improved particle swarm optimization

摘要：

　　A novel image segmentation algorithm based on fuzzy C-means (FCM) clustering and improved particle swarm optimization (PSO) is proposed.The algorithn takes global search results of improved PSO as the initialized values of the FCM,effectively avoiding easily trapping into local optimum of the traditional FCM and the premature convergence of PSO.Meanwhile,the algorithm takes the clustering centers as the reference to search scope of improved PSO algorithm for global searching that are obtained through hard C-means (HCM) algorithm for improving the velocity of the algorithm.The experimental results show the proposed algorithm can converge more quickly and segment the image more effectively than the traditional FCM algorithm.

关键词： image segmentation particle swarm optimization fuzzy C-means clustering

作者: Yue Yang Shuxu Guo Runlan Tian Peng Liu

作者单位: College of Electronic Science and Engineering,Jilin University, Changchun 130012, China Aviation Electronic Engineering Department,Aviation University of Air Force,Changchun 130022, China

会议类型: 国际会议

会议名称: 2012 2nd international Conference on Materials Science and Information Technology(2012第二届材料科学与信息技术国际会议)(MSIT2012)

会议地点: 西安

会议语种:英文

页码: 1553-1557

在线出版日期: 2012-08-24（万方平台首次上网日期，不代表论文的发表时间）