Signature recognition using artificial neural network

Nowadays, there are many applications required the user to confirm his identity. It might be done by asking a secret question that the user will answer to get into that application, and it might be a password or a pin code, face, eye, fingerprint or signature. Automatic signature verification is an...

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Main Authors: Abushariah, Ahmad A. M., Gunawan, Teddy Surya, Khalifa, Othman Omran, Chebil, Jalel
Format: Book Chapter
Language:English
Published: IIUM Press 2011
Subjects:
Online Access:http://irep.iium.edu.my/21660/1/Chapter_27.pdf
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author Abushariah, Ahmad A. M.
Gunawan, Teddy Surya
Khalifa, Othman Omran
Chebil, Jalel
author_facet Abushariah, Ahmad A. M.
Gunawan, Teddy Surya
Khalifa, Othman Omran
Chebil, Jalel
author_sort Abushariah, Ahmad A. M.
collection IIUM
description Nowadays, there are many applications required the user to confirm his identity. It might be done by asking a secret question that the user will answer to get into that application, and it might be a password or a pin code, face, eye, fingerprint or signature. Automatic signature verification is an active field of research with many practical applications. Automatic handwritten signature verification is divided into two approaches: off-line and on-line. In the off-line signature verification approach, the data of the signature is obtained from a static image utilizing a scanning device [I). For our application, off-line approach will be utilized.Neural Networks (NN) also known as Artificial Neural Networks (ANN) belong to the artificial intelligence approaches, which attempt to mechanize the recognition procedure according to the way a person applies intelligence in visualizing and analyzing[2]. Neural Networks' structure is inspired by biological models of the nervous system proposed as a model of the human brain's activities aiming to mimic certain processing capabilities of the human brain.
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spelling oai:generic.eprints.org:216602020-11-19T01:34:57Z http://irep.iium.edu.my/21660/ Signature recognition using artificial neural network Abushariah, Ahmad A. M. Gunawan, Teddy Surya Khalifa, Othman Omran Chebil, Jalel TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Nowadays, there are many applications required the user to confirm his identity. It might be done by asking a secret question that the user will answer to get into that application, and it might be a password or a pin code, face, eye, fingerprint or signature. Automatic signature verification is an active field of research with many practical applications. Automatic handwritten signature verification is divided into two approaches: off-line and on-line. In the off-line signature verification approach, the data of the signature is obtained from a static image utilizing a scanning device [I). For our application, off-line approach will be utilized.Neural Networks (NN) also known as Artificial Neural Networks (ANN) belong to the artificial intelligence approaches, which attempt to mechanize the recognition procedure according to the way a person applies intelligence in visualizing and analyzing[2]. Neural Networks' structure is inspired by biological models of the nervous system proposed as a model of the human brain's activities aiming to mimic certain processing capabilities of the human brain. IIUM Press 2011 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/21660/1/Chapter_27.pdf Abushariah, Ahmad A. M. and Gunawan, Teddy Surya and Khalifa, Othman Omran and Chebil, Jalel (2011) Signature recognition using artificial neural network. In: Human Behaviour Recognition, Identification and Computer Interaction. IIUM Press, Kuala Lumpur, pp. 255-262. ISBN 978-967-418-156-7 http://rms.research.iium.edu.my/bookstore/default.aspx
spellingShingle TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Abushariah, Ahmad A. M.
Gunawan, Teddy Surya
Khalifa, Othman Omran
Chebil, Jalel
Signature recognition using artificial neural network
title Signature recognition using artificial neural network
title_full Signature recognition using artificial neural network
title_fullStr Signature recognition using artificial neural network
title_full_unstemmed Signature recognition using artificial neural network
title_short Signature recognition using artificial neural network
title_sort signature recognition using artificial neural network
topic TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
url http://irep.iium.edu.my/21660/1/Chapter_27.pdf
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