%0 Journal Article
%T Fuzzy C-means image classification algorithm based on SSCL<br>基于SSCL的模糊C均值图像分类方法
%A liweiwei
%A liuchunping
%A wangzhaohui
%A zhangshukui
%A <br>李卫伟
%A 刘纯平
%A 王朝晖
%A 张书奎
%J 中国图象图形学报
%D 2011
%I 
%X An adaptive fuzzy C-means image classification algorithm based on SSCL is proposed, in order to overcome the shortcomings that traditional fuzzy C-means clustering algorithm is noise-sensitive and relies excessively on initial cluster centers. First we obtain the cluster centers using SSCL, then treat the cluster centers as the initial value of fuzzy C-means, so an adaptive image classification can be achieved. At last, post processing is implemented using space information. Experiment results show that proposed algorithm is less sensitive to noise and initial cluster centers in FCM method, and has better classification accuracy.
%K image segmentation
%K fuzzy C-means
%K self-splitting competitive learning<br>图像分割
%K 模糊C均值
%K 自分裂竞争学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=0B8B9577772EF0CFEC72D2550C0E2693&yid=9377ED8094509821&vid=7801E6FC5AE9020C&iid=0B39A22176CE99FB&sid=1B64850025D0BBBE&eid=1D67BE204FBF4800&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=9