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.
This research is partially supported by the HK-RGC grant, the ARC grant, the NSFC under Grant No. 60141002, and the ASFC under Grant No. 02I53073.
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© 2006 Springer-Verlag Berlin Heidelberg
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Xia, Y., Zhao, R., Zhang, Y., Sun, J., Feng, D. (2006). Texture Segmentation by Fuzzy Clustering of Spatial Patterns. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_111
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DOI: https://doi.org/10.1007/11881599_111
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45916-3
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