%0 Journal Article
%T Fuzzy clustering image segmentation algorithm based on CPSO<br>基于混沌粒子群和模糊聚类的图像分割算法*
%A ZHANG Xiao-hong
%A NING Hong-mei
%A <br>张小红
%A 宁红梅
%J 计算机应用研究
%D 2011
%I 
%X Fuzzy C-means(FCM) clustering algorithm was an effective image segmentation algorithm which combined the concept of fuzzy sets and unsupervised clustering. And it suited for the uncertain and ambiguous characteristic in intensity image. But it was sensitive to initial clustering center and membership matrix and likely converged into the local minimum, which caused the quality of image segmentation lower. By using of the properties-ergodicity, randomicity of chaos, this paper proposed a new image segmentation algorithm, which combined the chaos particle swarm optimization(CPSO) and FCM clustering. Experimental results prove this method not only has the ability to prevent the particles to convergence to local optimum because of standstill, but also has faster convergence and higher accuracy of segmentation.
%K image segmentation
%K chaos particle swarm optimization
%K fuzzy C-means clustering
%K global optimization<br>图像分割
%K 混沌粒子群算法
%K 模糊C-均值聚类
%K 全局优化
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=039278FEE09854C502EC64449DABF746&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=59906B3B2830C2C5&sid=91C62701AC047C45&eid=2962CBC248A73C99&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=14