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