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邻域灰度差加权的模糊C均值聚类图像分割算法
引用本文:沙秀艳,何友,王贞俭.邻域灰度差加权的模糊C均值聚类图像分割算法[J].火力与指挥控制,2008,33(12).
作者姓名:沙秀艳  何友  王贞俭
作者单位:1. 鲁东大学数学与信息学院,山东,烟台,264025;海军航空工程学院,山东,烟台,264001
2. 海军航空工程学院,山东,烟台,264001
3. 鲁东大学数学与信息学院,山东,烟台,264025
基金项目:国家自然科学基金资助项目 , 鲁东大学校基金资助项目  
摘    要:模糊C均值(FCM)算法用于灰度图像分割是一种非监督模糊聚类后再标定的过程,适合灰度图像中存在着模糊和不确定性的特点.但是这种算法没有考虑到样本空间中不同的样本点对分类的贡献不同,因此分割效果不理想.提出了邻域灰度差加权的模糊C均值聚类算法,实验结果表明,该算法不仅取得了很好的分割效果,而且加快了算法的收敛速度,从而满足了图像分割的有效性、实时性的要求.

关 键 词:图象分割  模糊C均值聚类  加权模糊C均值聚类  邻域灰度差

An Image Segmentation Algorithm of Weighted with Neighborhood Gray Difference Fuzzy C-means Clustering
SHA Xiu-yan,HE You,WANG Zhen-jian.An Image Segmentation Algorithm of Weighted with Neighborhood Gray Difference Fuzzy C-means Clustering[J].Fire Control & Command Control,2008,33(12).
Authors:SHA Xiu-yan  HE You  WANG Zhen-jian
Institution:SHA Xiu-yan1,2,HE You1,WANG Zhen-jian2 (1.School of Mathematics , Information,Ludong University,Yantai 264025,China,2.Naval Aeronautical Engineering Institute,Yantai 264001,China)
Abstract:It is a procedure of the label following an unsupervised fuzzy clustering that fuzzy c-means(FCM) algorithm is applied for gray image segmentation,and it suits for the uncertain and ambiguous characters in gray image.But this algorithm doesn't consider that different sample variously influences the result of the class in sample space.So the result isn't ideal.This paper introduces an image segmentation algorithm of weighted with neighborhood gray difference fuzzy C-means clustering.Experimental results demo...
Keywords:image segmentation  fuzzy C-means clustering(FCM)  weighed fuzzy C-means clustering(WFCM)  neighborhood gray difference  
本文献已被 CNKI 万方数据 等数据库收录!
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