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Signature recognition using artificial neural network

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

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Abstract

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.

Item Type: Book Chapter
Additional Information: 5588/21660
Uncontrolled Keywords: Signature recognition, artificial neural network
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 05 Sep 2012 16:25
Last Modified: 05 Sep 2012 16:26
URI: http://irep.iium.edu.my/id/eprint/21660

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