|
Título:
|
Unsupervised perceptual model for color image's segmentation
|
|
Autores:
|
Sobrevilla, P. ;
Gomez, D. ;
Montero, Javier ;
Montseny, E.
|
|
Tipo de documento:
|
texto impreso
|
|
Editorial:
|
IEEE, 2005
|
|
Dimensiones:
|
application/pdf
|
|
Nota general:
|
info:eu-repo/semantics/restrictedAccess
|
|
Idiomas:
|
|
|
Palabras clave:
|
Estado = Publicado
,
Materia = Ciencias: Matemáticas: Lógica simbólica y matemática
,
Tipo = Sección de libro
|
|
Resumen:
|
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.
|
|
En línea:
|
https://eprints.ucm.es/id/eprint/16938/1/Montero42.pdf
|
