An Improved FCM Algorithm for Image Segmentation

被引：0

作者：

Li, Kunlun ^{[1
]}

Cao, Zheng ^{[1
]}

Cao, Liping ^{[2
]}

Liu, Ming ^{[1
]}

机构：

[1] Hebei Univ, Coll Elect & Informat Engn, Baoding 071002, Peoples R China

[2] Baoding Vocat & Tech Coll, Dept Elect & Mech Engn, Baoding 071002, Peoples R China

来源：

ROUGH SET AND KNOWLEDGE TECHNOLOGY (RSKT) | 2010年 / 6401卷

基金：

中国国家自然科学基金;

关键词：

Fuzzy C-Means; Image Segmentation; Spatial Constraint;

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 novel image segmentation method based on modified fuzzy c-means (FCM) is proposed in this paper. By using the neighborhood pixels as spatial information, a spatial constraint penalty term is added in the objective function of standard FCM to improve the robustness. Meanwhile, the neighbor pixels information is used selectively to reduce computing time and iterations. Experiments on real images segmentation proved the availability of the improvement.

引用

页码：551 / 556

页数：6

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