Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification
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,...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-08-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/17/3709 |
| _version_ | 1828150173905190912 |
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| author | Lukas Kolda Ondrej Krejcar Ali Selamat Kamil Kuca Oluwaseun Fadeyi |
| author_facet | Lukas Kolda Ondrej Krejcar Ali Selamat Kamil Kuca Oluwaseun Fadeyi |
| author_sort | Lukas Kolda |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T21:40:42Z |
| format | Article |
| id | doaj.art-caa3d706603f48b4a0c73fe5170672f4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:40:42Z |
| publishDate | 2019-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-caa3d706603f48b4a0c73fe5170672f42022-12-22T04:01:37ZengMDPI AGSensors1424-82202019-08-011917370910.3390/s19173709s19173709Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless VerificationLukas Kolda0Ondrej Krejcar1Ali Selamat2Kamil Kuca3Oluwaseun Fadeyi4Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove 50003, Czech RepublicFaculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove 50003, Czech RepublicFaculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove 50003, Czech RepublicFaculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove 50003, Czech RepublicFaculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove 50003, Czech RepublicBiometric 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.https://www.mdpi.com/1424-8220/19/17/3709biometryidentificationbloodstreamimage recognitionmulti-biometrics |
| spellingShingle | Lukas Kolda Ondrej Krejcar Ali Selamat Kamil Kuca Oluwaseun Fadeyi Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification Sensors biometry identification bloodstream image recognition multi-biometrics |
| title | Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification |
| title_full | Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification |
| title_fullStr | Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification |
| title_full_unstemmed | Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification |
| title_short | Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification |
| title_sort | multi biometric system based on cutting edge equipment for experimental contactless verification |
| topic | biometry identification bloodstream image recognition multi-biometrics |
| url | https://www.mdpi.com/1424-8220/19/17/3709 |
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