Ali, M. Ameer; Karmakar, Gour C. and Dooley, Laurence S.
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|DOI (Digital Object Identifier) Link:||https://doi.org/10.1108/17563781011066684|
|Google Scholar:||Look up in Google Scholar|
Purpose - Existing shape-based fuzzy clustering algorithms are all designed to explicitly segment regular geometrically-shaped objects in an image, with the consequence that this restricts their capability to separate arbitrarily-shaped objects.
Design/Methodology/Approach – With the aim of separating arbitrary shaped objects in an image, this paper presents a new detection and separation of generic shaped objects (FKG) algorithm that analytically integrates arbitrary shape information into a fuzzy clustering framework, by introducing a shape constraint that preserves the original object shape during iterative scaling.
Findings - Both qualitative and numerical empirical results analysis corroborate the improved object segmentation performance achieved by the FKG strategy upon different image types and disparately shaped objects.
Originality/Value - The proposed FKG algorithm can be highly used in the applications where object segmentation is necessary. Like this algorithm can be applied in MPEG-4 for real object segmentation that is already applied in synthetic object segmentation.
|Item Type:||Journal Article|
|Copyright Holders:||2010 Emerald Group Publishing|
|Keywords:||fuzzy control; image processing; programming and algorithm theory|
|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:||16 Jul 2010 15:48|
|Last Modified:||05 Oct 2016 05:53|
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