Login / Signup

Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset.

Christof KaubaBernhard PrommeggerAndreas Uhl
Published in: Sensors (Basel, Switzerland) (2019)
Vascular pattern based biometric recognition is gaining more and more attention, with a trend towards contactless acquisition. An important requirement for conducting research in vascular pattern recognition are available datasets. These datasets can be established using a suitable biometric capturing device. A sophisticated capturing device design is important for good image quality and, furthermore, at a decent recognition rate. We propose a novel contactless capturing device design, including technical details of its individual parts. Our capturing device is suitable for finger and hand vein image acquisition and is able to acquire palmar finger vein images using light transmission as well as palmar hand vein images using reflected light. An experimental evaluation using several well-established vein recognition schemes on a dataset acquired with the proposed capturing device confirms its good image quality and competitive recognition performance. This challenging dataset, which is one of the first publicly available contactless finger and hand vein datasets, is published as well.
Keyphrases
  • image quality
  • deep learning
  • capillary electrophoresis
  • randomized controlled trial
  • rna seq
  • magnetic resonance imaging
  • optical coherence tomography
  • machine learning
  • magnetic resonance
  • mass spectrometry