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Offline signature verification system using hidden markov model (HMM) analysis of varying number of states and state transition topology

This paper describes the design and development of an offline signature verification system that is based on Hidden Markov Modeling (HMM) technique performed on a series of a localized direction feature extracted from a scanned signature image. It also describes the analysis of the testing results b...

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Bibliographic Details
Main Authors: Bakri N.B., Ahmad S.M.S., Shakil A.
Other Authors: 36805728300
Format: Article
Published: 2023
Subjects:
Hidden Markov
Offline Signature Biometrics
Biometrics
Image processing
Design and Development
Forged signature sample
Hidden Markov modeling
Number of state
Off-line signature verification
Signature images
State transitions
Testing results
Hidden Markov models
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id my.uniten.dspace-29672
record_format dspace
spelling my.uniten.dspace-296722023-12-28T15:30:43Z Offline signature verification system using hidden markov model (HMM) analysis of varying number of states and state transition topology Bakri N.B. Ahmad S.M.S. Shakil A. 36805728300 24721182400 24722081200 Hidden Markov Offline Signature Biometrics Biometrics Image processing Design and Development Forged signature sample Hidden Markov Hidden Markov modeling Number of state Off-line signature verification Offline Signature Biometrics Signature images State transitions Testing results Hidden Markov models This paper describes the design and development of an offline signature verification system that is based on Hidden Markov Modeling (HMM) technique performed on a series of a localized direction feature extracted from a scanned signature image. It also describes the analysis of the testing results by varying the number of HMM states (5, 6, 7, 8, 9 and 10 respectively) and their state transition topology. The testing reported in this paper has been carried out on signature samples of 100 users which contain both their genuine as well as their skilled and random forged signature samples counterparts. The chosen algorithm is simple to be implemented which results in fast verification operation, and at thesame time is reliable in detecting forgeries. � 2009 WASET.ORG. Final 2023-12-28T07:30:43Z 2023-12-28T07:30:43Z 2009 Article 2-s2.0-78651542927 https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651542927&partnerID=40&md5=575fbc1568c2d6a626e9be4a341f2ac6 https://irepository.uniten.edu.my/handle/123456789/29672 38 1220 1225 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
Offline Signature Biometrics
Biometrics
Image processing
Design and Development
Forged signature sample
Hidden Markov
Hidden Markov modeling
Number of state
Off-line signature verification
Offline Signature Biometrics
Signature images
State transitions
Testing results
Hidden Markov models
spellingShingle Hidden Markov
Offline Signature Biometrics
Biometrics
Image processing
Design and Development
Forged signature sample
Hidden Markov
Hidden Markov modeling
Number of state
Off-line signature verification
Offline Signature Biometrics
Signature images
State transitions
Testing results
Hidden Markov models
Bakri N.B.
Ahmad S.M.S.
Shakil A.
Offline signature verification system using hidden markov model (HMM) analysis of varying number of states and state transition topology
description This paper describes the design and development of an offline signature verification system that is based on Hidden Markov Modeling (HMM) technique performed on a series of a localized direction feature extracted from a scanned signature image. It also describes the analysis of the testing results by varying the number of HMM states (5, 6, 7, 8, 9 and 10 respectively) and their state transition topology. The testing reported in this paper has been carried out on signature samples of 100 users which contain both their genuine as well as their skilled and random forged signature samples counterparts. The chosen algorithm is simple to be implemented which results in fast verification operation, and at thesame time is reliable in detecting forgeries. � 2009 WASET.ORG.
author2 36805728300
author_facet 36805728300
Bakri N.B.
Ahmad S.M.S.
Shakil A.
format Article
author Bakri N.B.
Ahmad S.M.S.
Shakil A.
author_sort Bakri N.B.
title Offline signature verification system using hidden markov model (HMM) analysis of varying number of states and state transition topology
title_short Offline signature verification system using hidden markov model (HMM) analysis of varying number of states and state transition topology
title_full Offline signature verification system using hidden markov model (HMM) analysis of varying number of states and state transition topology
title_fullStr Offline signature verification system using hidden markov model (HMM) analysis of varying number of states and state transition topology
title_full_unstemmed Offline signature verification system using hidden markov model (HMM) analysis of varying number of states and state transition topology
title_sort offline signature verification system using hidden markov model (hmm) analysis of varying number of states and state transition topology
publishDate 2023
_version_ 1806423539930103808
score 13.222552

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