FCM Clustering Segmentation Algorithms Based on Spatial Constraint

被引：1

作者：

Tian Junwei ^{[1
]}

Yu Yalin ^{[2
]}

Shen Tao ^{[1
]}

机构：

[1] Xian Technol Univ, Sch Mech & Elect Engn, Xian 710032, Peoples R China

[2] Shenzhen Polaris etek Ltd Co, Shenzhen 710065, Peoples R China

来源：

PRECISION ENGINEERING AND NON-TRADITIONAL MACHINING | 2012年 / 411卷

关键词：

fuzzy c-means clustering (FCM); spatial constrained fuzzy c-means clustering (SCFCM); image segmentation; robustness; IMAGE SEGMENTATION; FUZZY; INFORMATION;

D O I：

10.4028/www.scientific.net/AMR.411.497

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In order to improve the performance of FCM clustering segmentation algorithm, a new spatial constrained FCM (SCFCM) algorithm is proposed. The new algorithm computes the membership degree of each pixel according to membership degrees of its neighbor pixels. For the purpose of enhance compute efficiency, two kinds of initial membership matrix creation algorithms are proposed to reduce iteration times. Experiments for a series of images are performed, according to the results, SCFCM clustering segmentation algorithm can restrain the noise effectively.

引用

页码：497 / +

页数：2

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