Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method

Multimodal identification, which exploits biometric information from more than one biometric modality, is more secure and reliable than unimodal identification. Face recognition and fingerprint recognition have received a lot of attention in recent years for their unique advantages. However, how to...

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Autores principales:	Qi Han, Heng Yang, Tengfei Weng, Guorong Chen, Jinyuan Liu, Yuan Tian
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	stability multimodal identification fingerprint recognition face recognition Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/90499071cfde43a3a627e9020a4bfe6d
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spelling	oai:doaj.org-article:90499071cfde43a3a627e9020a4bfe6d2021-11-25T18:17:44ZMultimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method10.3390/math92229762227-7390https://doaj.org/article/90499071cfde43a3a627e9020a4bfe6d2021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/22/2976https://doaj.org/toc/2227-7390Multimodal identification, which exploits biometric information from more than one biometric modality, is more secure and reliable than unimodal identification. Face recognition and fingerprint recognition have received a lot of attention in recent years for their unique advantages. However, how to integrate these two modalities and develop an effective multimodal identification system are still challenging problems. Hetero-associative memory (HAM) models store some patterns that can be reliably retrieved from other patterns in a robust way. Therefore, in this paper, face and fingerprint biometric features are integrated by the use of a hetero-associative memory method for multimodal identification. The proposed multimodal identification system can integrate face and fingerprint biometric features at feature level when the system converges to the state of asymptotic stability. In experiment 1, the predicted fingerprint by inputting an authorized user’s face is compared with the real fingerprint, and the matching rate of each group is higher than the given threshold. In experiment 2 and experiment 3, the predicted fingerprint by inputting the face of an unauthorized user and the stealing authorized user’s face is compared with its real fingerprint input, respectively, and the matching rate of each group is lower than the given threshold. The experimental results prove the feasibility of the proposed multimodal identification system.Qi HanHeng YangTengfei WengGuorong ChenJinyuan LiuYuan TianMDPI AGarticlestabilitymultimodal identificationfingerprint recognitionface recognitionMathematicsQA1-939ENMathematics, Vol 9, Iss 2976, p 2976 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	stability multimodal identification fingerprint recognition face recognition Mathematics QA1-939
spellingShingle	stability multimodal identification fingerprint recognition face recognition Mathematics QA1-939 Qi Han Heng Yang Tengfei Weng Guorong Chen Jinyuan Liu Yuan Tian Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method
description	Multimodal identification, which exploits biometric information from more than one biometric modality, is more secure and reliable than unimodal identification. Face recognition and fingerprint recognition have received a lot of attention in recent years for their unique advantages. However, how to integrate these two modalities and develop an effective multimodal identification system are still challenging problems. Hetero-associative memory (HAM) models store some patterns that can be reliably retrieved from other patterns in a robust way. Therefore, in this paper, face and fingerprint biometric features are integrated by the use of a hetero-associative memory method for multimodal identification. The proposed multimodal identification system can integrate face and fingerprint biometric features at feature level when the system converges to the state of asymptotic stability. In experiment 1, the predicted fingerprint by inputting an authorized user’s face is compared with the real fingerprint, and the matching rate of each group is higher than the given threshold. In experiment 2 and experiment 3, the predicted fingerprint by inputting the face of an unauthorized user and the stealing authorized user’s face is compared with its real fingerprint input, respectively, and the matching rate of each group is lower than the given threshold. The experimental results prove the feasibility of the proposed multimodal identification system.
format	article
author	Qi Han Heng Yang Tengfei Weng Guorong Chen Jinyuan Liu Yuan Tian
author_facet	Qi Han Heng Yang Tengfei Weng Guorong Chen Jinyuan Liu Yuan Tian
author_sort	Qi Han
title	Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method
title_short	Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method
title_full	Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method
title_fullStr	Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method
title_full_unstemmed	Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method
title_sort	multimodal identification based on fingerprint and face images via a hetero-associative memory method
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/90499071cfde43a3a627e9020a4bfe6d
work_keys_str_mv	AT qihan multimodalidentificationbasedonfingerprintandfaceimagesviaaheteroassociativememorymethod AT hengyang multimodalidentificationbasedonfingerprintandfaceimagesviaaheteroassociativememorymethod AT tengfeiweng multimodalidentificationbasedonfingerprintandfaceimagesviaaheteroassociativememorymethod AT guorongchen multimodalidentificationbasedonfingerprintandfaceimagesviaaheteroassociativememorymethod AT jinyuanliu multimodalidentificationbasedonfingerprintandfaceimagesviaaheteroassociativememorymethod AT yuantian multimodalidentificationbasedonfingerprintandfaceimagesviaaheteroassociativememorymethod
_version_	1718411395154837504

Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method

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