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Image segmentation using fuzzy clustering incorporating spatial information

Ali, Ameer; Karmakar, Gour C. and Dooley, Laurence S. (2004). Image segmentation using fuzzy clustering incorporating spatial information. In: International Conference on Artificial Intelligence and Applications (AIA '04), 16-18 February 2004, Innsbruck, Austria.

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Abstract

Effective image segmentation cannot be achieved for a fuzzy clustering algorithm based on using only pixel intensity, pixel locations or a combination of the two. Often if both pixel intensity and pixel location are combined, one feature tends to minimize the effect of other, thus degrading the resulting segmentation. This paper directly addresses this problem by introducing a new algorithm called image segmentation using fuzzy clustering incorporating spatial information (FCSI), which merges the segmented results independently generated by fuzzy clustering-based on pixel intensity and the location of pixels. Qualitative results show the superiority of the FCSI algorithm compared with the fuzzy c-means (FCM) algorithm for all three alternatives, clustering using only pixel intensity, pixel locations and a combination of the two.

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)
Item ID: 13072
Depositing User: Laurence Dooley
Date Deposited: 26 Feb 2009 11:55
Last Modified: 04 Aug 2016 16:31
URI: http://oro.open.ac.uk/id/eprint/13072
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