Feature-Weighted Mountain Method with Its Application to Color Image Segmentation

被引：0

作者：

Hung, Wen-Liang ^{[2
]}

Yang, Miin-Shen ^{[1
,3
]}

Yu, Jian ^{[4
]}

Hwang, Chao-Ming ^{[5
]}

机构：

[1] Chung Yuan Christian Univ, Dept Appl Math, Chungli 32023, Taiwan

[2] Natl Hsinchu Univ Educ, Grad Inst Comp Sci, Hsinchu, Taiwan

[3] Chung Yuan Christian Univ, Dept Appl Math, Chungli 32023, Taiwan

[4] Beijing Jiaotong Univ, Dept Comp Sci, Beijing, Peoples R China

[5] Chinese Culture Univ Yangminshan, Dept Appl Math, Taipei, Taiwan

来源：

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

关键词：

Mountain method; Feature weight; Color image segmentation;

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：

In this paper, we propose a feature-weighted mountain clustering method. The proposed method can work well when there are noisy feature variables and could be useful for obtaining initially estimated cluster centers for other clustering algorithms. Results from color image segmentation illustrate the proposed method actually produces better segmentation than previous methods.

引用

页码：537 / 544

页数：8

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