Integration of Fingerprint and Face Features for Multimodal Authentication

Unimodal biometric system is a biometric system that based only on one human trait. This type of biometric has been used in various applications. Even though this type of biometric system has good reliability and accuracy, this system also has several weaknesses due to illumination or enrolment prob...

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Main Author:	Nasir, Ilham
Format:	Thesis
Published:	2016
Subjects:	TK7800-8360 Electronics
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id	my-mmu-ep.6892
record_format	uketd_dc
spelling	my-mmu-ep.68922017-09-07T10:39:55Z Integration of Fingerprint and Face Features for Multimodal Authentication 2016-05 Nasir, Ilham TK7800-8360 Electronics Unimodal biometric system is a biometric system that based only on one human trait. This type of biometric has been used in various applications. Even though this type of biometric system has good reliability and accuracy, this system also has several weaknesses due to illumination or enrolment problem. In order to solve these problems, multimodal biometric system can be applied. Multimodal biometric system combines information from more than one human trait and deliver the decision. In this contrast, a number of studies have shown that multimodal biometric system can get better result compared with the unimodal system. Thus, the multimodal biometrics is an emerging area in biometric technology where more than one biometrics is combined to improve the performance and security. In this research, multimodal biometric system that combined face and fingerprint features is designed for robust user authentication. The first step in proposed framework is pre-processing to enhance the image quality. The next step is feature extraction which extracts the features from face and fingerprint image separately. 2016-05 Thesis http://shdl.mmu.edu.my/6892/ http://library.mmu.edu.my/diglib/onlinedb/dig_lib.php masters Multimedia University Faculty of Information Science and Technology
institution	Multimedia University
collection	MMU Institutional Repository
topic	TK7800-8360 Electronics
spellingShingle	TK7800-8360 Electronics Nasir, Ilham Integration of Fingerprint and Face Features for Multimodal Authentication
description	Unimodal biometric system is a biometric system that based only on one human trait. This type of biometric has been used in various applications. Even though this type of biometric system has good reliability and accuracy, this system also has several weaknesses due to illumination or enrolment problem. In order to solve these problems, multimodal biometric system can be applied. Multimodal biometric system combines information from more than one human trait and deliver the decision. In this contrast, a number of studies have shown that multimodal biometric system can get better result compared with the unimodal system. Thus, the multimodal biometrics is an emerging area in biometric technology where more than one biometrics is combined to improve the performance and security. In this research, multimodal biometric system that combined face and fingerprint features is designed for robust user authentication. The first step in proposed framework is pre-processing to enhance the image quality. The next step is feature extraction which extracts the features from face and fingerprint image separately.
format	Thesis
qualification_level	Master's degree
author	Nasir, Ilham
author_facet	Nasir, Ilham
author_sort	Nasir, Ilham
title	Integration of Fingerprint and Face Features for Multimodal Authentication
title_short	Integration of Fingerprint and Face Features for Multimodal Authentication
title_full	Integration of Fingerprint and Face Features for Multimodal Authentication
title_fullStr	Integration of Fingerprint and Face Features for Multimodal Authentication
title_full_unstemmed	Integration of Fingerprint and Face Features for Multimodal Authentication
title_sort	integration of fingerprint and face features for multimodal authentication
granting_institution	Multimedia University
granting_department	Faculty of Information Science and Technology
publishDate	2016
_version_	1747829642357637120

Integration of Fingerprint and Face Features for Multimodal Authentication

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