Unsupervised perceptual model for color image's segmentation



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Sobrevilla, P. and Gómez, D. and Montero, Javier and Montseny, E. (2005) Unsupervised perceptual model for color image's segmentation. In NAFIPS 2005 - 2005 Annual meeting of the north american fuzzy information processing society. IEE monograph series . IEEE, Detroit, MI, pp. 349-354. ISBN 0-7803-9187-X

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Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1548560


Color Segmentation is a fundamental, step in image understanding. Moreover, for getting accurate color image's segmentation algorithms, human being's perception of color should be considered. In this line we propose an unsupervised segmentation algorithm that is based on a fuzzy graph coloring process for representing the fuzzy color similarity degrees among neighboring pixels from a perceptual point of view. As main goal is to detect and extract the regions explaining the image, we stress the role of coloring procedures for unsupervised segmentation and fuzzy classification by means of useful, comprehensive and simple enough fuzzy graphical representations.

Item Type:Book Section
Additional Information:

Annual Meeting of the North-American-Fuzzy-Information-Processing-Society
JUN 26-28, 2005

Uncontrolled Keywords:Segmentation algorithms; Image classification; Coloring problem; Fuzzy sets; Perceptual vision
Subjects:Sciences > Mathematics > Logic, Symbolic and mathematical
ID Code:16938
Deposited On:31 Oct 2012 09:34
Last Modified:05 Sep 2018 16:37

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