%0 Journal Article
%T Research on fuzzy C-means clustering algorithm based on spatial weighted and its application<br>基于空间邻域加权的模糊C-均值聚类及其应用研究*
%A MENG Li-min
%A SONG Yu-qing
%A ZHU Feng
%A <br>孟丽敏
%A 宋余庆
%A 朱峰
%J 计算机应用研究
%D 2010
%I 
%X bstract:The application of C-means algorithm to image clustering is not taking into account spatial information apart from intensity values, which will lead a misclassification on the boundaries and inhomogeneous regions with noises. This paper proposed a new image clustering method using fuzzy C-means algorithm based on the spatial weighted. Firstly, defined a spatial information function to exploit the spatial information, which was not only effective to deal with noisy, but also reserve well edge property. Secondly, it designed the neighbourhood information weighted membership matrix with spatial contraints. Finally, applied this algorithm to synthetic image and simulated MR data clustering. The experimental results show that the proposed clustering scheme is effective for noisy image.
%K image clustering
%K fuzzy C-means clustering
%K spatial information<br>图像聚类
%K 模糊C-均值聚类
%K 空间邻域
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=CD27EA1AD8646AEA2F769078BA66970C&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=F3090AE9B60B7ED1&sid=68772F948FEE433C&eid=8C30F8AEECD30979&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=11