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New fuzzy rules for improved image segmentation

Karmakar, Gour; Dooley, Laurence and Murshed, Manzur (2002). New fuzzy rules for improved image segmentation. In: 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 13-17 May 2002, Orlando, Florida, USA.

DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1109/ICASSP.2002.5745678
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Abstract

The extended fuzzy rules for image segmentation (EFRIS) algorithm initially splits all segmented regions into mutually exclusive 4-connected objects, from which the largest one in each region is designated as its main object. A drawback of this approach is that it is less effective when the main objects are relatively small and some of the minor objects are completely surrounded and connected to the main object of another region. Besides, defining insufficient merging rules, EFRIS also only considers the surrounding main objects in the original order that the regions were segmented, which is undesirable. In this paper, a new general segmentation algorithm called modified extended fuzzy rules for image segmentation (MEFRIS) is presented, which addresses these problems and whose improved segmentation performance is analysed and numerically evaluated. The results are also contrasted with both the original generic fuzzy rule-based image segmentation (GFRIS) and EFRIS algorithms.

Item Type: Conference Item
Copyright Holders: 2002 IEEE
ISSN: 1520-6149
Extra Information: Published in 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing : Proceedings : May 13-17, 2002, Renaissance Orlando Resort, Orlando, Florida, USA, Piscataway, N. J., IEEE, 2002, pp. IV-4192, (ISBN. 0-7803-7402-9)

Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 28897
Depositing User: Laurence Dooley
Date Deposited: 06 Jun 2011 15:07
Last Modified: 06 Jun 2011 15:07
URI: http://oro.open.ac.uk/id/eprint/28897
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