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Anova-based feature analysis and selection in HMM-based offline signature verification system

This paper presents an analysis performance of different features in distinguishing between genuine and forged signatures for HMM based offline signature verification systems. The four offline features include pixel density, centre of gravity, distance and angle. All features considered are local in...

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Main Authors:	Balbed M.A.M., Ahmad S.M.S., Shakil A.
Other Authors:	24721384800
Format:	Conference Paper
Published:	2023
Subjects:	Hidden Markov models Industrial applications Intelligent systems Pixels Regression analysis Analysis techniques Center of gravity Centre of gravity Density features Feature analysis Off-line signature verification Offline Skilled forgery Analysis of variance (ANOVA)
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id	my.uniten.dspace-29678
record_format	dspace
spelling	my.uniten.dspace-296782024-04-17T10:36:26Z Anova-based feature analysis and selection in HMM-based offline signature verification system Balbed M.A.M. Ahmad S.M.S. Shakil A. 24721384800 24721182400 24722081200 Hidden Markov models Industrial applications Intelligent systems Pixels Regression analysis Analysis techniques Center of gravity Centre of gravity Density features Feature analysis Off-line signature verification Offline Skilled forgery Analysis of variance (ANOVA) This paper presents an analysis performance of different features in distinguishing between genuine and forged signatures for HMM based offline signature verification systems. The four offline features include pixel density, centre of gravity, distance and angle. All features considered are local in nature. The analysis technique used here is based on analysis of variance (ANOVA). Experimental results show that the combination of center of gravity and pixel density features are good for distinguishing between genuine and skilled forgeries for an HMM based offline signature verification system. � 2009 IEEE. Final 2023-12-28T07:30:45Z 2023-12-28T07:30:45Z 2009 Conference Paper 10.1109/CITISIA.2009.5224240 2-s2.0-70449103604 https://www.scopus.com/inward/record.uri?eid=2-s2.0-70449103604&doi=10.1109%2fCITISIA.2009.5224240&partnerID=40&md5=7206cc974cad80ebb3e6a74682f6287f https://irepository.uniten.edu.my/handle/123456789/29678 5224240 66 69 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	Hidden Markov models Industrial applications Intelligent systems Pixels Regression analysis Analysis techniques Center of gravity Centre of gravity Density features Feature analysis Off-line signature verification Offline Skilled forgery Analysis of variance (ANOVA)
spellingShingle	Hidden Markov models Industrial applications Intelligent systems Pixels Regression analysis Analysis techniques Center of gravity Centre of gravity Density features Feature analysis Off-line signature verification Offline Skilled forgery Analysis of variance (ANOVA) Balbed M.A.M. Ahmad S.M.S. Shakil A. Anova-based feature analysis and selection in HMM-based offline signature verification system
description	This paper presents an analysis performance of different features in distinguishing between genuine and forged signatures for HMM based offline signature verification systems. The four offline features include pixel density, centre of gravity, distance and angle. All features considered are local in nature. The analysis technique used here is based on analysis of variance (ANOVA). Experimental results show that the combination of center of gravity and pixel density features are good for distinguishing between genuine and skilled forgeries for an HMM based offline signature verification system. � 2009 IEEE.
author2	24721384800
author_facet	24721384800 Balbed M.A.M. Ahmad S.M.S. Shakil A.
format	Conference Paper
author	Balbed M.A.M. Ahmad S.M.S. Shakil A.
author_sort	Balbed M.A.M.
title	Anova-based feature analysis and selection in HMM-based offline signature verification system
title_short	Anova-based feature analysis and selection in HMM-based offline signature verification system
title_full	Anova-based feature analysis and selection in HMM-based offline signature verification system
title_fullStr	Anova-based feature analysis and selection in HMM-based offline signature verification system
title_full_unstemmed	Anova-based feature analysis and selection in HMM-based offline signature verification system
title_sort	anova-based feature analysis and selection in hmm-based offline signature verification system
publishDate	2023
_version_	1806426502877675520
score	13.222552

Anova-based feature analysis and selection in HMM-based offline signature verification system

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