Feature-weighted mountain method with its application to color image segmentation

Authors:
Wen-Liang Hung;Miin-Shen Yang;Jian Yu;Chao-Ming Hwang
Affiliations:
Graduate Institute of Computer Science, National Hsinchu University of Education, Hsin-Chu, Taiwan;Department of Applied Mathematics, Chung Yung Christian University, Chung-Li, Taiwan;Department of Computer Science, Beijing Jiaotong University, Beijing, China;Department of Applied Mathematics, Chinese Culture University Yangminshan, Taipei, Taiwan
Venue:
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Year:
2010

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Abstract

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.