Extracting features for the linguistic variables of fuzzy rules using hidden Markov model
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 Mark...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
American Institute of Physics
2007
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| Online Access: | http://psasir.upm.edu.my/id/eprint/57313/1/Extracting%20features%20for%20the%20linguistic%20variables%20of%20fuzzy%20rules%20using%20hidden%20Markov%20model.pdf http://psasir.upm.edu.my/id/eprint/57313/ |
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| Institution: | Universiti Putra Malaysia |
| Language: | English |
| Summary: | 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. |
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