Ali, M. A.; Karmakar, G. C. and Dooley, L. S.
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|DOI (Digital Object Identifier) Link:||https://doi.org/10.1109/ICME.2005.1521529|
|Google Scholar:||Look up in Google Scholar|
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.
|Item Type:||Conference Item|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Laurence Dooley|
|Date Deposited:||19 Aug 2008 06:31|
|Last Modified:||06 Oct 2016 14:18|
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Fuzzy image segmentation using shape information. (deposited 15 Apr 2008)
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