CONF Bros_BIOSIG_2021/IDIAP Vein Enhancement with Deep Auto-Encoders to improve Finger Vein Recognition Bros, Victor Kotwal, Ketan Marcel, Sébastien EXTERNAL http://publications.idiap.ch/attachments/papers/2021/Bros_BIOSIG_2021.pdf PUBLIC Biometrics Special Interest Group (BIOSIG 2021) 2021 978-3-88579-709-8 The field of Vascular Biometric Recognition has drawn a lot of attention recently with theemergence of new computer vision techniques. The different methods using Deep Learning involvea new understanding of deeper features from the vascular network. The specific architecture of theveins needs complex model capable of comprehending the vascular pattern. In this paper, we presentan image enhancement method using Deep Convolutional Neural Network. For this task, a residualconvolutional auto-encoder architecture has been trained in a supervised way to enhance the veinpatterns in near-infrared images. The method has been evaluated on several databases with promisingresults on the UTFVP database as a main result. In including the model as a preprocessing in thebiometric pipelines of recognition for finger vein patterns, the error rate has been reduced from 2.1%to 1.0%.