Publication:
Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model

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dc.citedby0
dc.contributor.authorSuliman A.en_US
dc.contributor.authorSulaiman M.N.en_US
dc.contributor.authorOthman M.en_US
dc.contributor.authorWirza R.en_US
dc.contributor.authorid25825739000en_US
dc.contributor.authorid22434244300en_US
dc.contributor.authorid56036884700en_US
dc.contributor.authorid35614233000en_US
dc.date.accessioned2023-12-29T07:56:42Z
dc.date.available2023-12-29T07:56:42Z
dc.date.issued2008
dc.description.abstractIn classifying handwritten characters, the stages prior to the classification phase play a role as major as the classification itself. This research work will be classifying the characters using a syntactical classification method namely fuzzy logic but will use the statistical method of Hidden Markov Model as an approach in extracting features for the linguistic variables of the fuzzy rule-based system. In this paper the feature extraction method will be highlighted and detailed. The HMM Model of a variable to be used in the classification system will be discussed. Experimental results from a few sample images show that the proposed technique is both effective and efficient to be used in extracting features for the linguistic variables of fuzzy rules. � 2008 American Institute of Physics.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1063/1.3037080
dc.identifier.epage33
dc.identifier.scopus2-s2.0-85040454820
dc.identifier.spage30
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85040454820&doi=10.1063%2f1.3037080&partnerID=40&md5=246084637c1db60c6a74120a5697b8a0
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30961
dc.identifier.volume1060
dc.pagecount3
dc.publisherAmerican Institute of Physics Inc.en_US
dc.relation.ispartofAll Open Access; Green Open Access
dc.sourceScopus
dc.sourcetitleAIP Conference Proceedings
dc.subjectFuzzy Logic
dc.subjectHandwritten Character Recognition
dc.subjectHMM Model
dc.subjectLinguistic Variable
dc.titleExtracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Modelen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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