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Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification

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dc.rights.license CC BY eng
dc.contributor.author Kolda, Lukáš cze
dc.contributor.author Krejcar, Ondřej cze
dc.contributor.author Selamat, Ali Bin cze
dc.contributor.author Kuča, Kamil cze
dc.date.accessioned 2020-06-01T11:05:20Z
dc.date.available 2020-06-01T11:05:20Z
dc.date.issued 2019 eng
dc.identifier.issn 1424-8220 eng
dc.identifier.uri http://hdl.handle.net/20.500.12603/311
dc.description.abstract Biometric verification methods have gained significant popularity in recent times, which has brought about their extensive usage. In light of theoretical evidence surrounding the development of biometric verification, we proposed an experimental multi-biometric system for laboratory testing. First, the proposed system was designed such that it was able to identify and verify a user through the hand contour, and blood flow (blood stream) at the upper part of the hand. Next, we detailed the hard and software solutions for the system. A total of 40 subjects agreed to be a part of data generation team, which produced 280 hand images. The core of this paper lies in evaluating individual metrics, which are functions of frequency comparison of the double type faults with the EER (Equal Error Rate) values. The lowest value was measured for the case of the modified Hausdorff distance metric - Maximally Helicity Violating (MHV). Furthermore, for the verified biometric characteristics (Hamming distance and MHV), appropriate and suitable metrics have been proposed and experimented to optimize system precision. Thus, the EER value for the designed multi-biometric system in the context of this work was found to be 5%, which proves that metrics consolidation increases the precision of the multi-biometric system. Algorithms used for the proposed multi-biometric device shows that the individual metrics exhibit significant accuracy but perform better on consolidation, with a few shortcomings. eng
dc.format Article number 3709 eng
dc.language.iso eng eng
dc.publisher MDPI eng
dc.relation.ispartof SENSORS, volume 19, issue: 17 eng
dc.subject biometry eng
dc.subject identification eng
dc.subject bloodstream eng
dc.subject image recognition eng
dc.subject multi-biometrics eng
dc.subject biometrie cze
dc.subject identifikace cze
dc.subject krevní oběh cze
dc.subject rozpoznávání obrazu cze
dc.subject multi-biometrie cze
dc.title Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification eng
dc.title.alternative Multi-biometrický systém založený na řezném okraji pro experimentální bezkontaktní ověření cze
dc.type article eng
dc.identifier.obd 43875479 eng
dc.identifier.wos 000486861900079 eng
dc.identifier.doi 10.3390/s19173709 eng
dc.description.abstract-translated Biometric verification methods have gained significant popularity in recent times, which has brought about their extensive usage. In light of theoretical evidence surrounding the development of biometric verification, we proposed an experimental multi-biometric system for laboratory testing. First, the proposed system was designed such that it was able to identify and verify a user through the hand contour, and blood flow (blood stream) at the upper part of the hand. Next, we detailed the hard and software solutions for the system. A total of 40 subjects agreed to be a part of data generation team, which produced 280 hand images. The core of this paper lies in evaluating individual metrics, which are functions of frequency comparison of the double type faults with the EER (Equal Error Rate) values. The lowest value was measured for the case of the modified Hausdorff distance metric - Maximally Helicity Violating (MHV). Furthermore, for the verified biometric characteristics (Hamming distance and MHV), appropriate and suitable metrics have been proposed and experimented to optimize system precision. Thus, the EER value for the designed multi-biometric system in the context of this work was found to be 5%, which proves that metrics consolidation increases the precision of the multi-biometric system. Algorithms used for the proposed multi-biometric device shows that the individual metrics exhibit significant accuracy but perform better on consolidation, with a few shortcomings. cze
dc.publicationstatus postprint eng
dc.peerreviewed yes eng
dc.source.url https://www.mdpi.com/1424-8220/19/17/3709 cze
dc.relation.publisherversion https://www.mdpi.com/1424-8220/19/17/3709 eng
dc.rights.access Open Access eng


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