Intelligent biometric signature verification system incorporating neural network

In this paper, the practical development of a novel but yet simple, low cost and userfriendly PC-based biometric technique to verify human signature is presented. The system is based on data acquired from time duration, pen position and pressure signals of handwritten signatures. A preprocessing sta...

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Main Authors: Lim, Boon Han, Mailah, Musa
Format: Article
Language:en
Published: Faculty of Mechanical Engineering 2005
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Online Access:http://eprints.utm.my/6492/1/LimBoonHan2005_Intelligent_biometric_signature_verification_system.pdf
http://eprints.utm.my/6492/
https://www.fkm.utm.my/~mekanika
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author Lim, Boon Han
Mailah, Musa
author_facet Lim, Boon Han
Mailah, Musa
author_sort Lim, Boon Han
building UTM Library
collection Institutional Repository
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
continent Asia
country Malaysia
description In this paper, the practical development of a novel but yet simple, low cost and userfriendly PC-based biometric technique to verify human signature is presented. The system is based on data acquired from time duration, pen position and pressure signals of handwritten signatures. A preprocessing stage of the acquired signature signals involving the use of a number of common feature extraction techniques is rigorously highlighted. An intelligent feature of the system is made possible through the application of a multilayer feedforward neural network that is used together with suitable algorithms to complement the verification process. The results of the study showed that the system is effective and promising in identifying correct human signatures presented to the system.
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institution Universiti Teknologi Malaysia
language en
publishDate 2005
publisher Faculty of Mechanical Engineering
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spelling my.utm.eprints-64922010-06-01T15:43:44Z http://eprints.utm.my/6492/ Intelligent biometric signature verification system incorporating neural network Lim, Boon Han Mailah, Musa TJ Mechanical engineering and machinery In this paper, the practical development of a novel but yet simple, low cost and userfriendly PC-based biometric technique to verify human signature is presented. The system is based on data acquired from time duration, pen position and pressure signals of handwritten signatures. A preprocessing stage of the acquired signature signals involving the use of a number of common feature extraction techniques is rigorously highlighted. An intelligent feature of the system is made possible through the application of a multilayer feedforward neural network that is used together with suitable algorithms to complement the verification process. The results of the study showed that the system is effective and promising in identifying correct human signatures presented to the system. Faculty of Mechanical Engineering 2005 Article PeerReviewed application/pdf en http://eprints.utm.my/6492/1/LimBoonHan2005_Intelligent_biometric_signature_verification_system.pdf Lim, Boon Han and Mailah, Musa (2005) Intelligent biometric signature verification system incorporating neural network. Jurnal Mekanikal (20). pp. 22-41. ISSN 0127-3396 https://www.fkm.utm.my/~mekanika
spellingShingle TJ Mechanical engineering and machinery
Lim, Boon Han
Mailah, Musa
Intelligent biometric signature verification system incorporating neural network
title Intelligent biometric signature verification system incorporating neural network
title_full Intelligent biometric signature verification system incorporating neural network
title_fullStr Intelligent biometric signature verification system incorporating neural network
title_full_unstemmed Intelligent biometric signature verification system incorporating neural network
title_short Intelligent biometric signature verification system incorporating neural network
title_sort intelligent biometric signature verification system incorporating neural network
topic TJ Mechanical engineering and machinery
url http://eprints.utm.my/6492/1/LimBoonHan2005_Intelligent_biometric_signature_verification_system.pdf
http://eprints.utm.my/6492/
https://www.fkm.utm.my/~mekanika
url_provider http://eprints.utm.my/