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

被引：0

作者：

Hung, Wen-Liang ^{[1
]}

Yang, Miin-Shen ^{[2
]}

Yu, Jian ^{[3
]}

Hwang, Chao-Ming ^{[4
]}

机构：

[1] Natl Hsinchu Univ Educ, Dept Appl Math, Hsinchu, Taiwan

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

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

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

来源：

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2011年 / 4卷 / 05期

关键词：

Mountain method; Feature weight; Color image segmentation;

D O I：

10.1080/18756891.2011.9727848

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 initial estimat of 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：1002 / 1011

页数：10

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