A region-based image segmentation method with kernel FCM

被引：0
|
作者：
Yang, Ai-min [1 ,2 ]
Zhou, Yong-mei [1 ]
Li, Xing-guang [1 ]
Tang, Min [2 ]
机构：
[1] Guangdong Univ Foreign Studies, Sch Informat, Guangzhou 510420, Guangdong, Peoples R China
[2] Hunan Univ Technol, Sch Comput & Commun, Hunan 412008, Peoples R China
来源：
FUZZY INFORMATION AND ENGINEERING, PROCEEDINGS | 2007年 / 40卷
关键词：
image segmentation; kernel fuzzy c-means clustering; feature extraction; region description;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A region-based image segmentation method with kernel fuzzy c-means clustering (FCM) is proposed. This method firstly extracts color, texture, and location features for each pixel by selecting suitable color space. Then, according to the feature vectors, pixeles are clustering by kernel FCM. The number and the center of clusters are decided by the proposed selecting the optimal cluster number method. Each pixel is grouped and labeled according to its membership degree. Finally, according to the pixels' neighbor connection theory, the regions with the same label are segmented again.
引用
收藏
页码：902 / +
页数：2
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