Art der Publikation: Beitrag in Zeitschrift

VPID: Towards Vein Pattern Identification Using Thermal Imaging

Autor(en):

Sarah Faltaous, Jonathan Liebers; Yomna Abdelrahman, Florian Alt; Schneegass, Stefan

Titel der Zeitschrift:

i-com

Veröffentlichung:

2019

Heftnummer:

18 (3)

Seiten:

259-270

Digital Object Identifier (DOI):

doi:10.1515/icom-2019-0009

Volltext:

VPID: Towards Vein Pattern Identification Using Thermal Imaging (6,62 MB)

Zitation:

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Kurzfassung

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.