Exponential-Distance Weighted K-Means Algorithm with Spatial Constraints for Color Image Segmentation

Author

Hung, Wen-Liang ; Yang, Miin-Shen ; Hwang, Chao-Ming

Author_Institution

Grad. Inst. of Comput. Sci., Nat. Hsinchu Univ. of Educ., Hsinchu, Taiwan

Volume

1

fYear

2011

fDate

14-15 May 2011

Firstpage

131

Lastpage

135

Abstract

The weighted k-means proposed by Huang et al. (2005) could automatically calculate feature weights. On theother hand, the fuzzy c-means (FCM) with spatial constraints(FCM_S) is an effective algorithm suitable for imagesegmentation. In this paper we propose a robust exponential distance weighted k-means (EDWkM) algorithm with spatialconstraints. The proposed algorithm is applied in color imagesegmentation. Several numerical and color image experimentsare performed to compare the EDWkM with existing methods.Experimental results show the effectiveness and superiority of the EDWkM algorithm.

Keywords

fuzzy set theory; image colour analysis; image segmentation; pattern clustering; color image segmentation; exponential distance weighted k-means algorithm; fuzzy c-means with spatial constraints; spatial constraints; Clustering algorithms; Color; Image segmentation; Noise measurement; Partitioning algorithms; Pixel; Robustness; Clustering; Color image segmentation; Exponential distance; K-means; Weighted k-means;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia and Signal Processing (CMSP), 2011 International Conference on

Conference_Location

Guilin, Guangxi

Print_ISBN

978-1-61284-314-8

Electronic_ISBN

978-1-61284-314-8

Type

conf

DOI

10.1109/CMSP.2011.33

Filename

5957393