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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Image Segmentation Based on FCM with Mahalanobis Distance
verfasst von : Yong Zhang, Zhuoran Li, Jingying Cai, Jianying Wang
Erschienen in: Information Computing and Applications
Verlag: Springer Berlin Heidelberg
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For its simplicity and applicability, fuzzy
c
-means clustering algorithm is widely used in image segmentation. However, fuzzy
c
-means clustering algorithm has some problems in image segmentation, such as sensitivity to noise, local convergence, etc. In order to overcome the fuzzy
c
-means clustering shortcomings, this paper replaces Euclidean distance with Mahalanobis distance in the fuzzy
c
-means clustering algorithm. Experimental results show that the proposed algorithm has a significant improvement on the effect and efficiency of segmentation comparing with the standard FCM clustering algorithm.