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Auflistung nach Schlagwort "Performance Evaluation"

1 - 4 von 4
  • Konferenzbeitrag
    Assessment of Sensor Ageing-Impact in Air Travelled Fingerprint Capturing Devices
    (BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Kauba, Christof; Kirchgasser, Simon; Jöchl, Robert; Uhl, Andreas
    Biometric recognition performance is affected by many factors, like varying acquisition conditions or ageing related effects, commonly denoted as biometric template ageing. Image sensor ageing, being part of biometric template ageing and a sub-field of image and video forensics, leads to defective pixels due to cosmic radiation, depending on the altitude. So far, image sensor ageing has only been a peripheral target in fingerprint research. We investigate the impact of image sensor ageing on various fingerprint capturing devices, including optical, capacitive and thermal ones. We established a fingerprint ageing dataset utilising 10 capturing devices which travelled on an air-plane for 127 days (to increase the number of developed defects). By evaluating the samples captured prior to their travel and afterwards using several state-of-the-art fingerprint quality metrics as well as minutiae-based fingerprint recognition systems we quantify the effect of image sensor ageing on fingerprint recognition. Furthermore, by employing a defect detection technique we quantify the number of defects developed during that period.
  • 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
    Methodological Principles for Reproducible Performance Evaluation in Cloud Computing
    (Software Engineering 2020, 2020) Papadopoulos, Alessandro V.; Versluis, Laurens; Bauer, André; Herbst, Nikolas; Kistowski, Jóakim von; Ali-Eldin, Ahmed; Abad, Cristina L.; Amaral, José Nelson; Tůma, Petr; Iosup, Alexandru
    In this work, we report on our recent article on \"Methodological Principles for Reproducible Performance Evaluation in Cloud Computing\" published in the IEEE Transactions on Software Engineering (TSE). This publication is a result of a joint effort coordinated by the Cloud Research Working Group of SPEC (Standard Performance Evaluation Corporation).
  • 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.