Publication: Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model
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Date
2008
Authors
Suliman A.
Sulaiman M.N.
Othman M.
Wirza R.
Journal Title
Journal ISSN
Volume Title
Publisher
American Institute of Physics Inc.
Abstract
In 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.
Description
Keywords
Fuzzy Logic , Handwritten Character Recognition , HMM Model , Linguistic Variable