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

被引：0

作者：

Hung W.-L. ^{[1
]}

Yang M.-S. ^{[2
]}

Yu J. ^{[3
]}

Hwang C.-M. ^{[4
]}

机构：

[1] Department of Applied Mathematics, National Hsinchu University of Education, Hsin-Chu

[2] Department of Applied Mathematics, Chung Yuan Christian University, Chung-Li

[3] Department of Computer Science, Beijing Jiaotong University, Beijing

[4] Department of Applied Mathematics, Chinese Culture University Yangminshan, Taipei

来源：

International Journal of Computational Intelligence Systems | 2011年 / 4卷 / 5期

关键词：

Color image segmentation; Feature weight; Mountain method;

D O I：

10.2991/ijcis.2011.4.5.23

中图分类号：

学科分类号：

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. © 2011, the authors.

引用

页码：1002 / 1011

页数：9

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