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Dooley, L. S.; Karmakar, G. C. and Murshed, M.
(2003).
DOI: https://doi.org/10.1109/ICIP.2003.1247128
URL: http://ieeexplore.ieee.org/search/wrapper.jsp?arnu...
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.
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- Item ORO ID
- 11477
- Item Type
- Conference or Workshop Item
- ISSN
- 1522-4880
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Centre for Research in Computing (CRC)
- Depositing User
- Laurence Dooley