Ali, M. A.; Karmakar, G. C. and Dooley, L. S.
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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 Item|
|Academic Unit/Department:||Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Laurence Dooley|
|Date Deposited:||19 Aug 2008 06:28|
|Last Modified:||24 Feb 2016 05:36|
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Available Versions of this Item
Fuzzy image segmentation using shape information. (deposited 17 Apr 2008)
Fuzzy Image Segmentation Using Generic Shape Cluster. (deposited 15 Apr 2008)
- Fuzzy image segmentation of generic shaped clusters. (deposited 19 Aug 2008 06:28) [Currently Displayed]
- Fuzzy Image Segmentation Using Generic Shape Cluster. (deposited 15 Apr 2008)
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