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

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...

Full description

Saved in:

Bibliographic Details
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
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my.uniten.dspace-30961
record_format	dspace
spelling	my.uniten.dspace-309612023-12-29T15:56:42Z Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model Suliman A. Sulaiman M.N. Othman M. Wirza R. 25825739000 22434244300 56036884700 35614233000 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. Final 2023-12-29T07:56:42Z 2023-12-29T07:56:42Z 2008 Conference paper 10.1063/1.3037080 2-s2.0-85040454820 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040454820&doi=10.1063%2f1.3037080&partnerID=40&md5=246084637c1db60c6a74120a5697b8a0 https://irepository.uniten.edu.my/handle/123456789/30961 1060 30 33 All Open Access; Green Open Access American Institute of Physics Inc. 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	Fuzzy Logic Handwritten Character Recognition HMM Model Linguistic Variable
spellingShingle	Fuzzy Logic Handwritten Character Recognition HMM Model Linguistic Variable Suliman A. Sulaiman M.N. Othman M. Wirza R. Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model
description	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.
author2	25825739000
author_facet	25825739000 Suliman A. Sulaiman M.N. Othman M. Wirza R.
format	Conference paper
author	Suliman A. Sulaiman M.N. Othman M. Wirza R.
author_sort	Suliman A.
title	Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model
title_short	Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model
title_full	Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model
title_fullStr	Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model
title_full_unstemmed	Extracting Features for the Linguistic Variables of Fuzzy Rules Using Hidden Markov Model
title_sort	extracting features for the linguistic variables of fuzzy rules using hidden markov model
publisher	American Institute of Physics Inc.
publishDate	2023
_version_	1806425760681951232
score	13.222552

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

Similar Items