Hybrid image segmentation using fuzzy c-means and gravitational search algorithm
In this paper, we propose a new hybrid approach for image segmentation. The proposed approach exploits spatial fuzzy c-means for clustering image pixels into homogeneous regions. In order to improve the performance of fuzzy c-means to cope with segmentation problems, we employ gravitational search a...
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| Main Authors: | , , , |
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| Format: | Book Section |
| Published: |
SPIE
2012
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| Subjects: | |
| Online Access: | http://eprints.utm.my/35802/ http://eprints.utm.my/35802/ http://eprints.utm.my/35802/ |
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| Summary: | In this paper, we propose a new hybrid approach for image segmentation. The proposed approach exploits spatial fuzzy c-means for clustering image pixels into homogeneous regions. In order to improve the performance of fuzzy c-means to cope with segmentation problems, we employ gravitational search algorithm which is inspired by Newton's rule of gravity. Gravitational search algorithm is incorporated into fuzzy c-means to take advantage of its ability to find optimum cluster centers which minimizes the fitness function of fuzzy c-means. Experimental results show effectiveness of the proposed method in segmentation different types of images as compared to classical fuzzy c-means. |
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