计算机工程与应用2009，Vol.45Issue(31)：158-160,3.DOI:10.3778/j.issn.1002-8331.2009.31.047
基于粒子群模糊C-均值聚类的图像分割算法
Image segmentation algorithm based on Particle Swarm Optimization fuzzy C-means clustering
摘要
Abstract
The Fuzzy C-Means(FCM) clustering algorithm is an effective image segmentation algorithm.But it is sensitive to initial clustering center and membership matrix and likely converges into the local minimum,which causes the quality of image segmentation lower.A new image segmentation algorithm is proposed, which combines the particle swarm optimization(PSO) and FCM clustering.Some experimental results are given,which show that the algorithm has the effective ability of searching global optimal solution.关键词
图像分割/粒子群优化算法/模糊C-均值聚类算法/全局优化Key words
image segmentation/Particle Swarm Optimization/Fuzzy C-mean clustering algorithm/global optimization分类
信息技术与安全科学引用本文复制引用
李丽丽,李明,刘希玉..基于粒子群模糊C-均值聚类的图像分割算法[J].计算机工程与应用,2009,45(31):158-160,3.基金项目
山东省自然科学基金重大项目(the Natural Science Foundation of Shandong Province of China under Grant No.Z2004G02) （the Natural Science Foundation of Shandong Province of China under Grant No.Z2004G02）
山东省教育厅计划项目(the Scientific and Technology Pmject of Shandong Education Bureau No.J05G01) （the Scientific and Technology Pmject of Shandong Education Bureau No.J05G01）
"泰山学者"建设工程专项经费资助("Taishan Scholar" Project of Shandong China). （"Taishan Scholar" Project of Shandong China）
