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Auflistung nach Autor:in "Davis, Stephen A."

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  • Konferenzbeitrag
    Application of affine-based reconstruction to retinal point patterns
    (BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Sadeghpour, Mahshid; Arakala, Arathi; Davis, Stephen A.; Horadam, Kathy J.
    Inverse biometrics that exploit the information of biometric references from comparison scores can compromise sensitive personal information of the users in biometric recognition systems. One inverse biometric method that has been very successful in regenerating face images applies an affine transformation to model the face recognition algorithm. This method is general and could apply to templates extracted from other biometric characteristics. This research proposes two formats to apply this method to spatial point patterns extracted from retina images and tests its performance on reconstructing such sparse templates. The results show that the quality of the reconstructed retina point pattern templates is lower than would be accepted by the system as mated.
  • Konferenzbeitrag
    Identification performance of evidential value estimation for fingermarks
    (BIOSIG 2015, 2015) Kotzerke, Johannes; Davis, Stephen A.; Hayes, Robert; Spreeuwers, Luuk J.; Veldhuis, Raymond N. J.; Horadam, Kathy J.
    Law enforcement agencies around the world use biometrics and fingerprints to solve and fight crime. Forensic experts are needed to record fingermarks at crime scenes and to ensure those captured are of evidential value. This process needs to be automated and streamlined as much as possible to improve efficiency and reduce workload. It has previously been demonstrated that is possible to estimate a fingermark's evidential value automatically for image captures taken with a mobile phone or other devices, such as a scanner or a high-quality camera. Here we study the relationship between a fingermark being of evidential value and its correct and certain identification and if it is possible to achieve identification despite the mark not having sufficient evidential value. Subsequently, we also investigate the influence the capture device used makes and if a mobile phone is an option worth considering. Our results show that automatic identification is possible for 126 of the 1 428 fin- , germarks captured by a mobile phone, of which 116 were marked as having evidential value by experts and 123 by an automated algorithm.