SOFT IMAGE SEGMENTATION BASED ON CENTER-FREE FUZZY CLUSTERING

Image segmentation remains one of the major challenges in image analysis. And soft image segmentation has been widely used due to its good effect. Fuzzy clustering algorithms are very popular in soft segmentation. A new soft image segmentation method based on center-free fuzzy clustering is proposed...

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Veröffentlicht in:Transactions of Nanjing University of Aeronautics & Astronautics 2013-03, Vol.30 (1), p.67-76
1. Verfasser: 马儒宁 朱燕 丁军娣
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Sprache:eng
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Zusammenfassung:Image segmentation remains one of the major challenges in image analysis. And soft image segmentation has been widely used due to its good effect. Fuzzy clustering algorithms are very popular in soft segmentation. A new soft image segmentation method based on center-free fuzzy clustering is proposed. The center-free fuzzy clus- tering is the modified version of the classical fuzzy C-means (FCM) clustering. Different from traditional fuzzy clustering, the center-free fuzzy clustering does not need to calculate the cluster center, so it can be applied to pair- wise relational data. In the proposed method, the mean-shift method is chosen for initial segmentation firstly, then the center-free clustering is used to merge regions and the final segmented images are obtained at last. Experimen- tal results show that the proposed method is better than other image segmentation methods based on traditional clustering.
ISSN:1005-1120