| Autor: |
Tuğçe Arıcan, Raymond Veldhuis, Luuk Spreeuwers, Loïc Bergeron, Christoph Busch, Ehsaneddin Jalilian, Christof Kauba, Simon Kirchgasser, Sébastien Marcel, Bernhard Prommegger, Kiran Raja, Raghavendra Ramachandra, Andreas Uhl |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
IET Biometrics, Vol 2024 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2047-4946 |
| DOI: |
10.1049/2024/3236602 |
| Popis: |
Finger vein recognition is gaining popularity in the field of biometrics, yet the inter-operability of finger vein patterns has received limited attention. This study aims to fill this gap by introducing a cross-device finger vein dataset and evaluating the performance of finger vein recognition across devices using a classical method, a convolutional neural network, and our proposed patch-based convolutional auto-encoder (CAE). The findings emphasise the importance of standardisation of finger vein recognition, similar to that of fingerprints or irises, crucial for achieving inter-operability. Despite the inherent challenges of cross-device recognition, the proposed CAE architecture in this study demonstrates promising results in finger vein recognition, particularly in the context of cross-device comparisons. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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