2026-08-20T06:01:31Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/531662024-11-27T15:14:13Zcom_20.500.14352_14col_20.500.14352_21
Docta Complutense
author
Sobrevilla, P.
author
Gómez González, Daniel
author
Montero De Juan, Francisco Javier
author
Montseny, E.
2023-06-20T13:38:35Z
2023-06-20T13:38:35Z
2005
Sobrevilla, P., Gomez, D., Montero, J., Montseny, E.: Unsupervised Perceptual Model for Color Image’s Segmentation. En: NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society. pp. 349-354. IEEE, Detroit, MI, USA (2005)
0-7803-9187-X
10.1109/NAFIPS.2005.1548560
https://hdl.handle.net/20.500.14352/53166
https//doi.org/10.1109/NAFIPS.2005.1548560
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.
eng
Unsupervised perceptual model for color image's segmentation
book part
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application/pdf
Montero42.pdf
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Montero42.pdf.txt