Title :
Unsupervised perceptual model for color image´s segmentation
Author :
Sobrevilla, P. ; Gomez, D. ; Montero, J. ; Montseny, E.
Author_Institution :
Applied. Math. II Dept., Tech. Univ. of Catalonia, Barcelona, Spain
Abstract :
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.
Keywords :
fuzzy set theory; graph colouring; image classification; image colour analysis; image segmentation; color image segmentation; color perception; fuzzy classification; fuzzy color similarity degree; fuzzy graph coloring process; fuzzy graphical representation; image detection; image extraction; perceptual vision; unsupervised perceptual model; unsupervised segmentation; Application software; Classification algorithms; Color; Computer vision; Fuzzy sets; Humans; Image segmentation; Pixel; Statistics; Stress; Segmentation algorithms; coloring problem; fuzzy sets; image classification; perceptual vision;
Conference_Titel :
Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American
Print_ISBN :
0-7803-9187-X
DOI :
10.1109/NAFIPS.2005.1548560