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Fuzzy based unsupervised segmentation of textured color images

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2 Author(s)
Xiaoyan Dai ; Dept. of Comput. Sci. & Syst. Eng., Muroran Inst. of Technol., Japan ; J. Maeda

This paper proposes a fuzzy-based unsupervised segmentation of textured color images. L*a*b* color space is used to represent color features and statistical geometrical features (SGF) are adopted as texture descriptors. Homogeneity decision makes a fusion of texture features and color features with fuzzy-rule theory. Hierarchical segmentation based on the fuzzy homogeneity decision is performed in four processes: hierarchical splitting, local agglomerative merging, global agglomerative merging and pixelwise classification. Experiments on segmentation of color texture mosaics and color natural images are presented to verify the effectiveness of the proposed approach in obtaining rough segmentation.

Published in:

Image Processing. 2002. Proceedings. 2002 International Conference on  (Volume:3 )

Date of Conference:

24-28 June 2002