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Wild, Peter; Radu, Petru; Chen, Lulu; Ferryman, James (2016)
Publisher: Elsevier
Journal: Pattern Recognition
Languages: English
Types: Article
Subjects: Computer Vision and Pattern Recognition, Software, Signal Processing, Artificial Intelligence

Classified by OpenAIRE into

ACM Ref: ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS
Anti-spoofing is attracting growing interest in biometrics, considering the variety of fake materials and new means to attack biometric recognition systems. New unseen materials continuously challenge state-of-the-art spoofing detectors, suggesting for additional systematic approaches to target anti-spoofing. By incorporating liveness scores into the biometric fusion process, recognition accuracy can be enhanced, but traditional sum-rule based fusion algorithms are known to be highly sensitive to single spoofed instances. This paper investigates 1-median filtering as a spoofing-resistant generalised alternative to the sum-rule targeting the problem of partial multibiometric spoofing where m out of n biometric sources to be combined are attacked. Augmenting previous work, this paper investigates the dynamic detection and rejection of livenessrecognition pair outliers for spoofed samples in true multi-modal configuration with its inherent challenge of normalisation. As a further contribution, bootstrap aggregating (bagging) classifiers for fingerprint spoof-detection algorithm is presented. Experiments on the latest face video databases (Idiap Replay- Attack Database and CASIA Face Anti-Spoofing Database), and fingerprint spoofing database (Fingerprint Liveness Detection Competition 2013) illustrate the efficiency of proposed techniques.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • Peter Wild received his Ph.D. degree in computer science with “sub-auspiciispraesidentis” honours (2013) from the University of Salzburg, where he held positions as Research Assistant (2007-2012) and Postdoc (2013). Currently, he is Postdoc in computer vision at the University of Reading. His research was awarded the European Biometrics Industry Award 2013.
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