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Auflistung nach Autor:in "Kauba, Christof"

1 - 6 von 6
  • Konferenzbeitrag
    Advanced variants of feature level fusion for finger vein recognition
    (Biosig 2016, 2016) Kauba, Christof; Piciucco, Emanuela; Maiorana, Emanuele; Campisi, Patrizio; Uhl, Andreas
  • 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
    PROTECT Multimodal DB: fusion evaluation on a novel multimodal biometrics dataset envisaging Border Control
    (BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Sequeira, Ana F.; Chen, Lulu; Ferryma, James; Galdi, Chiara; Chiesa, Valeria; Dugelay, Jean-Luc; Maik, Patryk; Gmitrowicz, Piotr; Szklarski, Lukasz; Prommegger, Bernhard; Kauba, Christof; Kirchgasser, Simon; Uhl, Andreas; Grudzien, Artur; Kowalski, Marcin
    This work presents a novel multimodal database comprising 3D face, 2D face, thermal face, visible iris, finger and hand veins, voice and anthropometrics. This dataset will constitute a valuable resource to the field with its number and variety of biometric traits. Acquired in the context of the EU PROTECT project, the dataset allows several combinations of biometric traits and envisages applications such as border control. Based upon the results of the unimodal data, a fusion scheme was applied to ascertain the recognition potential of combining these biometric traits in a multimodal approach. Due to the variability on the discriminative power of the traits, a leave the n-best out fusion technique was applied to obtain different recognition results.
  • Konferenzbeitrag
    Robustness evaluation of hand vein recognition systems
    (BIOSIG 2015, 2015) Kauba, Christof; Uhl, Andreas
    Hand vein recognition systems are more robust against external influences which degrade the image quality like dust or dirt on the sensor or skin surface conditions than fingerprint ones. We investigate the robustness of several hand vein feature extraction and matching schemes against different types of image distortions, related to conditions occurring during the acquisition of hand vein images. These distortions correspond to sensor defects, bad system design and problems in the use of the sensor. The impact on the recognition accuracy is quantified in terms of the EER and compared across different schemes and different types of distortions.
  • 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.