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| Segmentation by Fusion of Self-Adaptive SFCM Cluster in Multi-Color Space Components
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Full
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Complete Issue PDF(9.16MB) |
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Volume: 6 Issue: 2 |
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Pages: |
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Publication
Date: April 2012 |
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ISSN
(Online): 1985-2304 |
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Pages |
157 - 166 |
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Author(s) |
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Published
Date |
16-04-2012 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
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| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Color Image Segmentation, Histogram, SFCM, Fusion |
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| This paper proposes a new, simple, and efficient segmentation approach that could find diverse applications in pattern recognition as well as in computer vision, particularly in color image segmentation. First, we choose the best segmentation components among six different color spaces. Then, Histogram and SFCM techniques are applied for initialization of segmentation. Finally, we 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, such as Mean-Shift, FCR and CTM, etc, our method could yield reasonably good or better image partitioning, which illustrates practical value of the method. |
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| kun chen : Colleagues
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| Yan Ma : Colleagues
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| Jun Liu : Colleagues
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