Automatic person identification system using handwritten signatures

This paper reports the design, implementation, and evaluation of a research work for developing an automatic person identification system using hand signatures biometric. The developed automatic person identification system mainly used toolboxes provided by MATLAB environment. . In order to train an...

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Main Authors:	Abushariah, Ahmad A. M., Gunawan, Teddy Surya, Chebil, Jalel, Abushariah, Mohammad Abd-Alrahman Mahmoud
Format:	Conference or Workshop Item
Language:	English
Published:	2012
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://irep.iium.edu.my/27192/ http://irep.iium.edu.my/27192/ http://irep.iium.edu.my/27192/3/Ahmad1280_Signature_Identification_v2.pdf

id	iium-27192
recordtype	eprints
spelling	iium-271922012-12-04T06:14:56Z http://irep.iium.edu.my/27192/ Automatic person identification system using handwritten signatures Abushariah, Ahmad A. M. Gunawan, Teddy Surya Chebil, Jalel Abushariah, Mohammad Abd-Alrahman Mahmoud TA Engineering (General). Civil engineering (General) This paper reports the design, implementation, and evaluation of a research work for developing an automatic person identification system using hand signatures biometric. The developed automatic person identification system mainly used toolboxes provided by MATLAB environment. . In order to train and test the developed automatic person identification system, an in-house hand signatures database is created, which contains hand signatures of 100 persons (50 males and 50 females) each of which is repeated 30 times. Therefore, a total of 3000 hand signatures are collected. The collected hand signatures have gone through pre-processing steps such as producing a digitized version of the signatures using a scanner, converting input images type to a standard binary images type, cropping, normalizing images size, and reshaping in order to produce a ready-to-use hand signatures database for training and testing the automatic person identification system. Global features such as signature height, image area, pure width, and pure height are then selected to be used in the system, which reflect information about the structure of the hand signature image. For features training and classification, the Multi-Layer Perceptron (MLP) architecture of Artificial Neural Network (ANN) is used. This paper also investigates the effect of the persons’ gender on the overall performance of the system. For performance optimization, the effect of modifying values of basic parameters in ANN such as the number of hidden neurons and the number of epochs are investigated in this work. The handwritten signature data collected from male persons outperformed those collected from the female persons, whereby the system obtained average recognition rates of 76.20% and74.20% for male and female persons, respectively. Overall, the handwritten signatures based system obtained an average recognition rate of 75.20% for all persons. 2012-07-03 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/27192/3/Ahmad1280_Signature_Identification_v2.pdf Abushariah, Ahmad A. M. and Gunawan, Teddy Surya and Chebil, Jalel and Abushariah, Mohammad Abd-Alrahman Mahmoud (2012) Automatic person identification system using handwritten signatures. In: International Conference on Computer and Communication Engineering (ICCCE 2012), 3-5 July 2012, Seri Pacific Hotel Kuala Lumpur. http://www.iium.edu.my/iccce/12/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Abushariah, Ahmad A. M. Gunawan, Teddy Surya Chebil, Jalel Abushariah, Mohammad Abd-Alrahman Mahmoud Automatic person identification system using handwritten signatures
description	This paper reports the design, implementation, and evaluation of a research work for developing an automatic person identification system using hand signatures biometric. The developed automatic person identification system mainly used toolboxes provided by MATLAB environment. . In order to train and test the developed automatic person identification system, an in-house hand signatures database is created, which contains hand signatures of 100 persons (50 males and 50 females) each of which is repeated 30 times. Therefore, a total of 3000 hand signatures are collected. The collected hand signatures have gone through pre-processing steps such as producing a digitized version of the signatures using a scanner, converting input images type to a standard binary images type, cropping, normalizing images size, and reshaping in order to produce a ready-to-use hand signatures database for training and testing the automatic person identification system. Global features such as signature height, image area, pure width, and pure height are then selected to be used in the system, which reflect information about the structure of the hand signature image. For features training and classification, the Multi-Layer Perceptron (MLP) architecture of Artificial Neural Network (ANN) is used. This paper also investigates the effect of the persons’ gender on the overall performance of the system. For performance optimization, the effect of modifying values of basic parameters in ANN such as the number of hidden neurons and the number of epochs are investigated in this work. The handwritten signature data collected from male persons outperformed those collected from the female persons, whereby the system obtained average recognition rates of 76.20% and74.20% for male and female persons, respectively. Overall, the handwritten signatures based system obtained an average recognition rate of 75.20% for all persons.
format	Conference or Workshop Item
author	Abushariah, Ahmad A. M. Gunawan, Teddy Surya Chebil, Jalel Abushariah, Mohammad Abd-Alrahman Mahmoud
author_facet	Abushariah, Ahmad A. M. Gunawan, Teddy Surya Chebil, Jalel Abushariah, Mohammad Abd-Alrahman Mahmoud
author_sort	Abushariah, Ahmad A. M.
title	Automatic person identification system using handwritten signatures
title_short	Automatic person identification system using handwritten signatures
title_full	Automatic person identification system using handwritten signatures
title_fullStr	Automatic person identification system using handwritten signatures
title_full_unstemmed	Automatic person identification system using handwritten signatures
title_sort	automatic person identification system using handwritten signatures
publishDate	2012
url	http://irep.iium.edu.my/27192/ http://irep.iium.edu.my/27192/ http://irep.iium.edu.my/27192/3/Ahmad1280_Signature_Identification_v2.pdf
first_indexed	2023-09-18T20:40:26Z
last_indexed	2023-09-18T20:40:26Z
_version_	1777409328565714944

Automatic person identification system using handwritten signatures

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