Abstract
This work presents an automated contactless fingerprint recognition system for smartphones. We provide a comprehensive description of the entire recognition pipeline and discuss important requirements for a fully automated capturing system. In addition, our implementation is made publicly available for research purposes. During a database acquisition, a total number of 1360 contactless and contact-based samples of 29 subjects are captured in two different environmental situations. Experiments on the acquired database show a comparable performance of our contactless scheme and the contact-based baseline scheme under constrained environmental influences. A comparative usability study on both capturing device types indicates that the majority of subjects prefer the contactless capturing method. Based on our experimental results, we analyze the impact of the current COVID-19 pandemic on fingerprint recognition systems. Finally, implementation aspects of contactless fingerprint recognition are summarized.
Funder
National Research Center for Applied Cybersecurity ATHENE
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
21 articles.
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1. Decentralized Federated Learning Links for Biometric Recognition;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
2. Exploring the Enabling Technologies of Contactless Fingerprint Reader;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28
3. MCLFIQ: Mobile Contactless Fingerprint Image Quality;IEEE Transactions on Biometrics, Behavior, and Identity Science;2024-04
4. Improving Sensor Interoperability between Contactless and Contact-Based Fingerprints Using Pose Correction and Unwarping;IET Biometrics;2023-12-18
5. New Finger Photo Databases with Presentation Attacks and Demographics;2023 IEEE International Conference on Big Data (BigData);2023-12-15