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Open AccessArticle

Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network

Department of Measurement and Electronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland
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Sensors 2020, 20(19), 5695; https://doi.org/10.3390/s20195695
Received: 14 August 2020 / Revised: 18 September 2020 / Accepted: 26 September 2020 / Published: 6 October 2020
(This article belongs to the Special Issue Biometric Sensing)
Devices and systems secured by biometric factors became a part of our lives because they are convenient, easy to use, reliable, and secure. They use information about unique features of our bodies in order to authenticate a user. It is possible to enhance the security of these devices by adding supplementary modality while keeping the user experience at the same level. Palm vein systems are based on infrared wavelengths used for capturing images of users’ veins. It is both convenient for the user, and it is one of the most secure biometric solutions. The proposed system uses IR and UV wavelengths; the images are then processed by a deep convolutional neural network for extraction of biometric features and authentication of users. We tested the system in a verification scenario that consisted of checking if the images collected from the user contained the same biometric features as those in the database. The True Positive Rate (TPR) achieved by the system when the information from the two modalities were combined was 99.5% by the threshold of acceptance set to the Equal Error Rate (EER). View Full-Text
Keywords: biometrics; palm vein scanner; multimodality; convolutional neural networks biometrics; palm vein scanner; multimodality; convolutional neural networks
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Stanuch, M.; Wodzinski, M.; Skalski, A. Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network. Sensors 2020, 20, 5695.

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