Signature verification system based on multiple classifiers and multi fusion decision approach

With an increase in identity fraud and the emphasis on security, there is growing and urgent need to verify human identify efficiently. Signature and the handwriting verification application are used in many fields such as banking, public sectors. Documents and cheques verification system has trigge...

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Main Author:	Mokayed, Hamam M. Ibrahim
Format:	Thesis
Language:	English
Published:	2010
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/11302/6/HamamM.IbrahimMFKE2010.pdf
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id	my-utm-ep.11302
record_format	uketd_dc
spelling	my-utm-ep.113022017-09-18T07:24:45Z Signature verification system based on multiple classifiers and multi fusion decision approach 2010-01 Mokayed, Hamam M. Ibrahim TK Electrical engineering. Electronics Nuclear engineering With an increase in identity fraud and the emphasis on security, there is growing and urgent need to verify human identify efficiently. Signature and the handwriting verification application are used in many fields such as banking, public sectors. Documents and cheques verification system has triggered a real need for reliable, accurate and robust system. This work adopts different classification techniques between the local features based and the global features based of the signature system in addition to different fusion techniques between the outputs of the different classifiers and global features based to improve error rate of behavioral system. Main goal is to develop more accurate and robust signature verification system than the previous developed system with False Rejection Rate (FRR) equals to 5.3 and False Acceptance Rate (FAR) equals to 0. To achieve this goal, first multiple classification techniques are applied to the signature verification system which are artificial neural network, support vector machine and Pearson correlation and then these techniques are fused by applying two complicated fusion techniques which are fuzzy logic and sequential fuzzy logic and one simple fusion technique which is max voting. Lastly the rule-based decision is applied to specify whether the signature is genuine or not. Second, the improved signature verification system is extended with the high performance Hitachi system. This biometric based system can be realized in many real world and web based applications where there is a need for higher security and robust identification. 2010-01 Thesis http://eprints.utm.my/id/eprint/11302/ http://eprints.utm.my/id/eprint/11302/6/HamamM.IbrahimMFKE2010.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Mokayed, Hamam M. Ibrahim Signature verification system based on multiple classifiers and multi fusion decision approach
description	With an increase in identity fraud and the emphasis on security, there is growing and urgent need to verify human identify efficiently. Signature and the handwriting verification application are used in many fields such as banking, public sectors. Documents and cheques verification system has triggered a real need for reliable, accurate and robust system. This work adopts different classification techniques between the local features based and the global features based of the signature system in addition to different fusion techniques between the outputs of the different classifiers and global features based to improve error rate of behavioral system. Main goal is to develop more accurate and robust signature verification system than the previous developed system with False Rejection Rate (FRR) equals to 5.3 and False Acceptance Rate (FAR) equals to 0. To achieve this goal, first multiple classification techniques are applied to the signature verification system which are artificial neural network, support vector machine and Pearson correlation and then these techniques are fused by applying two complicated fusion techniques which are fuzzy logic and sequential fuzzy logic and one simple fusion technique which is max voting. Lastly the rule-based decision is applied to specify whether the signature is genuine or not. Second, the improved signature verification system is extended with the high performance Hitachi system. This biometric based system can be realized in many real world and web based applications where there is a need for higher security and robust identification.
format	Thesis
qualification_level	Master's degree
author	Mokayed, Hamam M. Ibrahim
author_facet	Mokayed, Hamam M. Ibrahim
author_sort	Mokayed, Hamam M. Ibrahim
title	Signature verification system based on multiple classifiers and multi fusion decision approach
title_short	Signature verification system based on multiple classifiers and multi fusion decision approach
title_full	Signature verification system based on multiple classifiers and multi fusion decision approach
title_fullStr	Signature verification system based on multiple classifiers and multi fusion decision approach
title_full_unstemmed	Signature verification system based on multiple classifiers and multi fusion decision approach
title_sort	signature verification system based on multiple classifiers and multi fusion decision approach
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2010
url	http://eprints.utm.my/id/eprint/11302/6/HamamM.IbrahimMFKE2010.pdf
_version_	1747814837962932224

Signature verification system based on multiple classifiers and multi fusion decision approach

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