DocumentCode :
2310788
Title :
A fuzzy rule-based colour image segmentation algorithm
Author :
Dooley, Laurence S. ; Karmakar, Gour C. ; Murshed, Manzur
Author_Institution :
Gippsland Sch. of Comput. & Inf. Technol., Monash Univ., Clayton, Vic., Australia
Volume :
1
fYear :
2003
fDate :
14-17 Sept. 2003
Abstract :
Most fuzzy rule-based image segmentation techniques to date have been primarily developed for gray level images. In this paper, a new algorithm called fuzzy rule-based colour image segmentation (FRCIS) is proposed by extending the generic fuzzy rule-based image segmentation (GFFUS) algorithm G.C. Karmakar, L.S. Dooley [2002] and integrating a novel algorithm for averaging hue angles. Qualitative and quantitative analysis of the performance of FRCIS is examined and contrasted with the popular fuzzy c-means (FCM) and possibilistic c-means (PCM) algorithms for both the hue-saturation-value (HSV) and RGB colour models. Overall, FRCIS provides considerable improvement for many different image types.
Keywords :
fuzzy logic; image colour analysis; image segmentation; RGB colour model; fuzzy c-means algorithm; fuzzy rule-based colour image segmentation; gray level image; hue angle averaging; hue-saturation-value; possibilistic c-means algorithm; red, green, blue colour; Algorithm design and analysis; Fuzzy systems; Humans; Image color analysis; Image segmentation; Information technology; Particle measurements; Phase change materials; Polynomials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-7750-8
Type :
conf
DOI :
10.1109/ICIP.2003.1247128
Filename :
1247128
Link To Document :
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