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Fuzzy image segmentation of generic shaped clusters

Ali, M. A.; Karmakar, G. C. and Dooley, L. S. (2005). Fuzzy image segmentation of generic shaped clusters. In: IEEE International Conference Image Processing (ICIP 2005), 11-14 Sep 2005, Genoa, Italy.

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The segmentation performance of any clustering algorithm is very sensitive to the features in an image, which ultimately restricts their generalisation capability. This limitation was the primary motivation in our investigation into using shape information to improve the generality of these algorithms. Fuzzy shape-based clustering techniques already consider ring and elliptical profiles in segmentation, though most real objects are neither ring nor elliptically shaped. This paper addresses this issue by introducing a new shape-based algorithm called fuzzy image segmentation of generic shaped clusters (FISG) that incorporates generic shape information into the framework of the fuzzy c-means (FCM) algorithm. Both qualitative and quantitative analyses confirm the superiority of FISG compared to other shape-based fuzzy clustering methods including, Gustafson-Kessel algorithm, ring-shaped, circular shell, c-ellipsoidal shells and elliptic ring-shaped clusters. The new algorithm has also been shown to be application independent so it can be applied in areas such as video object plane segmentation in MPEG-4 based coding.

Item Type: Conference or Workshop Item
Academic Unit/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)
Item ID: 11403
Depositing User: Laurence Dooley
Date Deposited: 19 Aug 2008 06:28
Last Modified: 03 May 2019 09:37
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