A Fuzzy Approach to Texture Segmentation

Authors:
Madasu Hanmandlu;Vamsi Krishna Madasu;Shantaram Vasikarla
Affiliations:
-;-;-
Venue:
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Year:
2004

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Abstract

The texture segmentation techniques arediversified by the existence of several approaches. Inthis paper, we propose fuzzy features for thesegmentation of texture image. For this purpose, amembership function is constructed to represent theeffect of the neighboring pixels on the current pixel in awindow. Using these membership function values, wefind a feature by weighted average method for thecurrent pixel. This is repeated for all pixels in thewindow treating each time one pixel as the currentpixel. Using these fuzzy based features, we derive threedescriptors such as maximum, entropy, and energy foreach window. To segment the texture image, themodified mountain clustering that is unsupervised andFuzzy C-means clustering have been used. Theperformance of the proposed features is compared withthat of fractal features.