Affiliation:
1. 27170 University of Duisburg-Essen , Essen , Germany
2. 240143 Bundeswehr University Munich , Munchen , Germany
Abstract
Abstract
Biometric authentication received considerable attention lately. The vein pattern on the back of the hand is a unique biometric that can be measured through thermal imaging. Detecting this pattern provides an implicit approach that can authenticate users while interacting. In this paper, we present the Vein-Identification system, called VPID. It consists of a vein pattern recognition pipeline and an authentication part. We implemented six different vein-based authentication approaches by combining thermal imaging and computer vision algorithms. Through a study, we show that the approaches achieve a low false-acceptance rate (“FAR”) and a low false-rejection rate (“FRR”). Our findings show that the best approach is the Hausdorff distance-difference applied in combination with a Convolutional Neural Networks (CNN) classification of stacked images.
Subject
Computer Networks and Communications,Human-Computer Interaction,Communication,Business, Management and Accounting (miscellaneous),Information Systems,Social Psychology
Cited by
4 articles.
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