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

• Main Authors: Suliman A., Sulaiman M.N., Othman M., Wirza R.
• Other Authors: 25825739000
• Format: Conference paper
• Published: American Institute of Physics Inc. 2023
• Subjects: Fuzzy Logic; Handwritten Character Recognition; HMM Model; Linguistic Variable

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.