Logo des Repositoriums

Auflistung nach Schlagwort "Finger Vein Scanner Device"

1 - 2 von 2
  • Konferenzbeitrag
    Longitudinal Finger Rotation - Problems and Effects in Finger-Vein Recognition
    (BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Prommegger, Bernhard; Kauba, Christof; Uhl, Andreas
    Finger-vein scanners or vein-based biometrics in general are becoming more and more popular. Commercial off-the-shelf finger-vein scanners usually capture only one finger from the palmar side using transillumination. Most scanners have a contact area and a finger-shaped support where the finger has to be placed onto in order to prevent misplacements of the finger including shifts, planar rotation and tilts. However, this is not able to prevent rotation of the finger along its longitudinal axis (also called non-planar finger rotation). This kind of finger rotation poses a severe problem in finger-vein recognition as the resulting vein image may represent entirely different patterns due to the perspective projection. We evaluated the robustness of several finger-vein recognition schemes against longitudinal finger rotation. Therefore, we established a finger-vein data set exhibiting longitudinal finger rotation in steps of 1° covering a range of 90°. Our experimental results confirm that the performance of most of the simple recognition schemes rapidly decreases for more than 10° of rotation, while more advanced schemes are able to handle up to 30°.
  • Konferenzbeitrag
    The Two Sides of the Finger - An Evaluation on the Recognition Performance of Dorsal vs. Palmar Finger-Veins
    (BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Kauba, Christof; Prommegger, Bernhard; Uhl, Andreas
    Vascular pattern (vein) based biometrics, especially finger- and hand-vein recognition gain more and more attention. In finger-vein recognition, the images are usually captured from the palmar (bottom) side of the finger. Dorsal (top) side finger vein recognition has not got much attention so far. In this paper we establish a new, publicly available, two-sided (dorsal and palmar) finger-vein data set. The data set is captured using two custom designed finger vein scanners, one based on near-infrared LED illumination, the other one on near-infrared laser modules. A recognition performance comparison between the single subsets (palmar and dorsal) as well as cross-subset (palmar vs. dorsal) comparison is conducted using several well-established finger-vein recognition schemes. The experimental results confirm that the palmar side achieves the overall best recognition performance but in general the dorsal side works better due to inherent finger texture information.