Hybrid of HMM and Fuzzy Logic for handwritten character recognition

This paper presents a hybrid approach of HMM and Fuzzy Logic in the field of handwritten character recognition. Fuzzy Logic is used in the recognition phase while HMM is used in the process of extracting features for the preparation of linguistic variables of the fuzzy rules. Experimental results fr...

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Main Authors: Suliman A., Shakil A., Sulaiman Md.N., Othman M., Wirza R.
Other Authors: 25825739000
Format: Conference paper
Published: 2023
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spelling my.uniten.dspace-309012023-12-29T15:55:32Z Hybrid of HMM and Fuzzy Logic for handwritten character recognition Suliman A. Shakil A. Sulaiman Md.N. Othman M. Wirza R. 25825739000 24722081200 22434244300 56036884700 35614233000 Character recognition Computational linguistics Feature extraction Fuzzy sets Fuzzy systems Hidden Markov models Information technology Extracting features Handwritten character recognitions Handwritten characters Hybrid approaches Linguistic variables Recognition rates Fuzzy logic This paper presents a hybrid approach of HMM and Fuzzy Logic in the field of handwritten character recognition. Fuzzy Logic is used in the recognition phase while HMM is used in the process of extracting features for the preparation of linguistic variables of the fuzzy rules. Experimental results from a few sample images give a reasonable recognition rate on a more challenging database of lower-case handwritten characters. This proved the proposed hybrid of the two techniques are compatible and can be used to complement each other effectively. � 2008 IEEE. Final 2023-12-29T07:55:32Z 2023-12-29T07:55:32Z 2008 Conference paper 10.1109/ITSIM.2008.4631674 2-s2.0-57349119966 https://www.scopus.com/inward/record.uri?eid=2-s2.0-57349119966&doi=10.1109%2fITSIM.2008.4631674&partnerID=40&md5=960579994ef775eed81c67ec88b0b8fe https://irepository.uniten.edu.my/handle/123456789/30901 2 4631674 All Open Access; Green Open Access Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Character recognition
Computational linguistics
Feature extraction
Fuzzy sets
Fuzzy systems
Hidden Markov models
Information technology
Extracting features
Handwritten character recognitions
Handwritten characters
Hybrid approaches
Linguistic variables
Recognition rates
Fuzzy logic
spellingShingle Character recognition
Computational linguistics
Feature extraction
Fuzzy sets
Fuzzy systems
Hidden Markov models
Information technology
Extracting features
Handwritten character recognitions
Handwritten characters
Hybrid approaches
Linguistic variables
Recognition rates
Fuzzy logic
Suliman A.
Shakil A.
Sulaiman Md.N.
Othman M.
Wirza R.
Hybrid of HMM and Fuzzy Logic for handwritten character recognition
description This paper presents a hybrid approach of HMM and Fuzzy Logic in the field of handwritten character recognition. Fuzzy Logic is used in the recognition phase while HMM is used in the process of extracting features for the preparation of linguistic variables of the fuzzy rules. Experimental results from a few sample images give a reasonable recognition rate on a more challenging database of lower-case handwritten characters. This proved the proposed hybrid of the two techniques are compatible and can be used to complement each other effectively. � 2008 IEEE.
author2 25825739000
author_facet 25825739000
Suliman A.
Shakil A.
Sulaiman Md.N.
Othman M.
Wirza R.
format Conference paper
author Suliman A.
Shakil A.
Sulaiman Md.N.
Othman M.
Wirza R.
author_sort Suliman A.
title Hybrid of HMM and Fuzzy Logic for handwritten character recognition
title_short Hybrid of HMM and Fuzzy Logic for handwritten character recognition
title_full Hybrid of HMM and Fuzzy Logic for handwritten character recognition
title_fullStr Hybrid of HMM and Fuzzy Logic for handwritten character recognition
title_full_unstemmed Hybrid of HMM and Fuzzy Logic for handwritten character recognition
title_sort hybrid of hmm and fuzzy logic for handwritten character recognition
publishDate 2023
_version_ 1806424183585898496
score 13.222552