A fuzzy rule-based colour image segmentation algorithm

Dooley, L. S.; Karmakar, G. C. and Murshed, M. (2003). A fuzzy rule-based colour image segmentation algorithm. In: IEEE International Conference on Image Processing (ICIP '03),, 14-17 Sep 2003, Barcelona.

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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About

• 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