Texture segmentation by fuzzy clustering of spatial patterns

Authors:
Yong Xia;Rongchun Zhao;Yanning Zhang;Jian Sun;Dagan Feng
Affiliations:
School of Computer, Northwestern Polytechnical University, Xi'an, China;School of Computer, Northwestern Polytechnical University, Xi'an, China;School of Computer, Northwestern Polytechnical University, Xi'an, China;School of Automatic Control, Northwestern Polytechnical University, Xi'an, China;School of Information Technologies, F09, University of Sydney, NSW, Australia
Venue:
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Year:
2006

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Abstract

An approach to perceptual segmentation of textured images by fuzzy clustering of spatial patterns is proposed in this paper. The dissimilarity between a texture feature, which is modeled as a spatial pattern, and each cluster is calculated as a combination of the Euclidean distance in the feature space and the spatial dissimilarity, which reflects how much of the pattern's neighborhood is occupied by other clusters. The proposed algorithm has been applied to the segmentation of texture mosaics. The results of comparative experiments demonstrate that the proposed approach can segment textured images more effectively and provide more robust segmentations.