Integrated biometric verification system using soft computing approach

Among various biometric verification systems, fingerprint verification is one of the most reliable and widely accepted. One essential part of fingerprint verification is the minutiae extraction system. Most existing minutiae extraction methods require image preprocessing or post processing resulting...

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Main Authors:	Abdul Rahman, Abdul Wahab, Ng, G. S., Jonathan, A.
Format:	Article
Language:	English
Published:	Kluwer Academic Publishers-Plenum Publishers 2007
Subjects:	T57 Applied mathematics. Quantitative methods. Operation research. System analysis
Online Access:	http://irep.iium.edu.my/38172/ http://irep.iium.edu.my/38172/ http://irep.iium.edu.my/38172/ http://irep.iium.edu.my/38172/1/Integrated_Biometric_Verification_System_Using_Soft_Computing_Approach.pdf

id	iium-38172
recordtype	eprints
spelling	iium-381722014-09-10T07:18:37Z http://irep.iium.edu.my/38172/ Integrated biometric verification system using soft computing approach Abdul Rahman, Abdul Wahab Ng, G. S. Jonathan, A. T57 Applied mathematics. Quantitative methods. Operation research. System analysis Among various biometric verification systems, fingerprint verification is one of the most reliable and widely accepted. One essential part of fingerprint verification is the minutiae extraction system. Most existing minutiae extraction methods require image preprocessing or post processing resulting in additional complex computation and time. Hence, direct gray-scale minutiae extraction approach on the image is preferred. One of these approaches is the use of Fuzzy Neural Network (FNN) as a recognition system to detect the presence of minutiae pattern. Currently, the development of FNN as a tool of recognition has shown a promising prospect. Some researchers have proposed several types of FNN. In particular, a Generic Self Organizing Fuzzy Neural Network (GENSOFNN) has been shown to excel in comparison with other FNN. Therefore, a new approach to perform direct grayscale minutiae extraction based on GENSOFNN is proposed in this paper. Experimental results show the potential of using GENSOFNN for real-time point of sale (POS) terminal for verification. Kluwer Academic Publishers-Plenum Publishers 2007 Article PeerReviewed application/pdf en http://irep.iium.edu.my/38172/1/Integrated_Biometric_Verification_System_Using_Soft_Computing_Approach.pdf Abdul Rahman, Abdul Wahab and Ng, G. S. and Jonathan, A. (2007) Integrated biometric verification system using soft computing approach. Neural Processing Letters, 25 (2). pp. 111-126. ISSN 1370-4621 (P), 1573-773X (O) http://link.springer.com/article/10.1007/s11063-006-9024-7 10.1007/s11063-006-9024-
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T57 Applied mathematics. Quantitative methods. Operation research. System analysis
spellingShingle	T57 Applied mathematics. Quantitative methods. Operation research. System analysis Abdul Rahman, Abdul Wahab Ng, G. S. Jonathan, A. Integrated biometric verification system using soft computing approach
description	Among various biometric verification systems, fingerprint verification is one of the most reliable and widely accepted. One essential part of fingerprint verification is the minutiae extraction system. Most existing minutiae extraction methods require image preprocessing or post processing resulting in additional complex computation and time. Hence, direct gray-scale minutiae extraction approach on the image is preferred. One of these approaches is the use of Fuzzy Neural Network (FNN) as a recognition system to detect the presence of minutiae pattern. Currently, the development of FNN as a tool of recognition has shown a promising prospect. Some researchers have proposed several types of FNN. In particular, a Generic Self Organizing Fuzzy Neural Network (GENSOFNN) has been shown to excel in comparison with other FNN. Therefore, a new approach to perform direct grayscale minutiae extraction based on GENSOFNN is proposed in this paper. Experimental results show the potential of using GENSOFNN for real-time point of sale (POS) terminal for verification.
format	Article
author	Abdul Rahman, Abdul Wahab Ng, G. S. Jonathan, A.
author_facet	Abdul Rahman, Abdul Wahab Ng, G. S. Jonathan, A.
author_sort	Abdul Rahman, Abdul Wahab
title	Integrated biometric verification system using soft computing approach
title_short	Integrated biometric verification system using soft computing approach
title_full	Integrated biometric verification system using soft computing approach
title_fullStr	Integrated biometric verification system using soft computing approach
title_full_unstemmed	Integrated biometric verification system using soft computing approach
title_sort	integrated biometric verification system using soft computing approach
publisher	Kluwer Academic Publishers-Plenum Publishers
publishDate	2007
url	http://irep.iium.edu.my/38172/ http://irep.iium.edu.my/38172/ http://irep.iium.edu.my/38172/ http://irep.iium.edu.my/38172/1/Integrated_Biometric_Verification_System_Using_Soft_Computing_Approach.pdf
first_indexed	2023-09-18T20:54:48Z
last_indexed	2023-09-18T20:54:48Z
_version_	1777410232642699264

Integrated biometric verification system using soft computing approach

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