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Published Articles >> Table of Contents >> Abstract
International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1
p. 636
A Fuzzy Approach to Texture Segmentation
Madasu Hanmandlu, I.I.T. Delhi, India
Vamsi Krishna Madasu, University of Queensland, Australia
Shantaram Vasikarla, American InterContinental University, Los Angeles, CA
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ITCC.2004.1286537
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| Abstract |
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The texture segmentation techniques are
diversified by the existence of several approaches. In
this paper, we propose fuzzy features for the
segmentation of texture image. For this purpose, a
membership function is constructed to represent the
effect of the neighboring pixels on the current pixel in a
window. Using these membership function values, we
find a feature by weighted average method for the
current pixel. This is repeated for all pixels in the
window treating each time one pixel as the current
pixel. Using these fuzzy based features, we derive three
descriptors such as maximum, entropy, and energy for
each window. To segment the texture image, the
modified mountain clustering that is unsupervised and
Fuzzy C-means clustering have been used. The
performance of the proposed features is compared with
that of fractal features.
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 Additional Information
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Index Terms- Texture, fractal dimension, modified mountain clustering, potential, validity, segmentation
Citation:
Madasu Hanmandlu, Vamsi Krishna Madasu, Shantaram Vasikarla,
"A Fuzzy Approach to Texture Segmentation,"
itcc,
p. 636,
International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1,
2004
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