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Segmentation of gray scale image based on intuitionistic fuzzy sets constructed from several membership functions
journal contribution
posted on 2014-12-01, 00:00 authored by V P Ananthi, P Balasubramaniam, Chee Peng LimChee Peng LimSegmentation is the process of extraction of objects from an image. This paper proposes a new algorithm to construct intuitionistic fuzzy set (IFS) from multiple fuzzy sets as an application to image segmentation. Hesitation degree in IFS is formulated as the degree of ignorance (due to the lack of knowledge) to determine whether the chosen membership function is best for image segmentation. By minimizing entropy of IFS generated from various fuzzy sets, an image is thresholded. Experimental results are provided to show the effectiveness of the proposed method.
History
Journal
Pattern RecognitionVolume
47Issue
12Pagination
3870 - 3880Publisher
Elsevier BVLocation
Amsterdam , NetherlandsPublisher DOI
ISSN
0031-3203Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2014, Elsevier BVUsage metrics
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Keywords
Hesitation degreeIntuitionistic fuzzy setMembership functionThresholdingScience & TechnologyTechnologyComputer Science, Artificial IntelligenceEngineering, Electrical & ElectronicComputer ScienceEngineeringRESTRICTED EQUIVALENCE FUNCTIONSTHRESHOLD SELECTION METHODENTROPYHISTOGRAMALGORITHMFUZZINESSInformation SystemsArtificial Intelligence and Image Processing
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