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Unsupervised perceptual model for color image's segmentation



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Sobrevilla, P. y Gómez, D. y Montero, Javier y 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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URL Oficial: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1548560

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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.

Tipo de documento:Sección de libro
Información Adicional:

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

Palabras clave:Segmentation algorithms; Image classification; Coloring problem; Fuzzy sets; Perceptual vision
Materias:Ciencias > Matemáticas > Lógica simbólica y matemática
Código ID:16938
Depositado:31 Oct 2012 09:34
Última Modificación:22 Abr 2016 14:05

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