A self-adaptive segmentation method by fusion of multi-color space components

Authors:
Kun Chen;Yan Ma;Jun Liu;Shun-bao Li
Affiliations:
Department of Information Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai, China;Department of Information Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai, China;Department of Information Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai, China;Department of Mathematic & Science, Shanghai Normal University, Shanghai, China
Venue:
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
Year:
2012

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Abstract

This paper presents a new, simple, and efficient segmentation approach. Firstly, choose the best segmentation components among six different color spaces. Then, Histogram and SFCM techniques are applied for initialization of segmentation. Finally, fuse the segmentation results and merge similar regions. Extensive experiments have been taken on Berkeley image database by using the proposed algorithm. The results show that, compared with some classical segmentation algorithms, our method could achieve better image partitioning and better performance.