Abstract
In this research, we present a new way of thinking using a Convolutional Neural Network (CNN) for palm-vein biometric authentication. In contrary to fingerprint and face, palm vein patterns are internal features which make them very hard to replicate. The objective of this research is to examine the possibility of a contactless authentication of individuals by imply a series of palm veins photographs taken by a camera in the near infrared. Biometric systems based on palm veins are considered very promising for high security environments. In mean time, deep learning techniques have assisted in image classification and tasks retrieval. The use of palm vein recognition through deep learning based methods and Convolutional Neural Network architectures (i.e., Inception V3 and SmallerVggNet) applications.
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Chantaf, S., Hilal, A., Elsaleh, R. (2020). Palm Vein Biometric Authentication Using Convolutional Neural Networks. In: Bouhlel, M., Rovetta, S. (eds) Proceedings of the 8th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT’18), Vol.1. SETIT 2018. Smart Innovation, Systems and Technologies, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-030-21005-2_34
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DOI: https://doi.org/10.1007/978-3-030-21005-2_34
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