DocumentCode
2642330
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
fYear
2005
fDate
26-28 June 2005
Firstpage
349
Lastpage
354
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American
Print_ISBN
0-7803-9187-X
Type
conf
DOI
10.1109/NAFIPS.2005.1548560
Filename
1548560
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