Ali, M. A.; Dooley, L. S. and Karmakar, G. C.
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|DOI (Digital Object Identifier) Link:||http://doi.org/10.1109/ITCC.2005.157|
|Google Scholar:||Look up in Google Scholar|
Results from any existing clustering algorithm that are used for segmentation are highly sensitive to features that limit their generalization. Shape is one important attribute of an object. The detection and separation of an object using fuzzy ring-shaped clustering (FKR) and elliptic ring-shaped clustering (FKE) already exists in the literature. Not all real objects however, are ring or elliptical in shape, so to address these issues, this paper introduces a new shape-based algorithm, called fuzzy image segmentation combining ring and elliptic shaped clustering algorithms (FCRE) by merging the initial segmented results produced by FKR and FKE. The distribution of unclassified pixels is performed by connectedness and fuzzy c-means (FCM) using a combination of pixel intensity and normalized pixel location. Both qualitative and quantitative analysis of the results for different varieties of images proves the superiority of the proposed FCRE algorithm compared with both FKR and FKE.
|Item Type:||Conference Item|
|Extra Information:||ISBN: 0-7695-2315-3|
|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:||12 Sep 2008 01:41|
|Last Modified:||04 Oct 2016 14:22|
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