Fuzzy image segmentation using shape information

Ali, M. A.; Karmakar, G. C. and Dooley, L. S. (2005). Fuzzy image segmentation using shape information. In: IEEE International Conference on Multimedia and Expo 2005 (ICME 2005), 6-8 Jul 2005, Amsterdam.

DOI: https://doi.org/10.1109/ICME.2005.1521529

URL: http://ieeexplore.ieee.org/search/wrapper.jsp?arnu...

Abstract

Results of any clustering algorithm are highly sensitive to features that limit their generalization and hence provide a strong motivation to integrate shape information into the algorithm. Existing fuzzy shape-based clustering algorithms consider only circular and elliptical shape information and consequently do not segment well, arbitrary shaped objects. To address this issue, this paper introduces a new shape-based algorithm, called fuzzy image segmentation using shape information (FISS) by incorporating general shape information. Both qualitative and quantitative analysis proves the superiority of the new FISS algorithm compared to other well-established shape-based fuzzy clustering algorithms, including Gustafson-Kessel, ring-shaped, circular shell, c-ellipsoidal shells and elliptic ring-shaped clusters.

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About

• Item ORO ID
• 11402
• Item Type
• Conference or Workshop Item
• 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