Multi-Biometric System Based on Cutting-Edge Equipment for Experimental Contactless Verification
| Autor: | Oluwaseun Fadeyi, Kamil Kuca, Ali Selamat, Lukas Kolda, Ondrej Krejcar |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
bloodstream
Biometrics Computer science Word error rate biometry 020206 networking & telecommunications Context (language use) 02 engineering and technology lcsh:Chemical technology Biochemistry Atomic and Molecular Physics and Optics Article Analytical Chemistry Hausdorff distance image recognition Metric (mathematics) 0202 electrical engineering electronic engineering information engineering identification 020201 artificial intelligence & image processing lcsh:TP1-1185 Electrical and Electronic Engineering multi-biometrics Instrumentation Algorithm |
| Zdroj: | Sensors, Vol 19, Iss 17, p 3709 (2019) Sensors Volume 19 Issue 17 Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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