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Face Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Features

Siegmund, Dirk ; Kerckhoff, Florian ; Yeste Magdaleno, Javier ; Jansen, Nils ; Kirchbuchner, Florian ; Kuijper, Arjan (2020):
Face Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Features.
In: BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, pp. 207-214,
Gesellschaft für Informatik, 19th International Conference of the Biometrics Special Interest Group, virtual Conference, 16.-18.09.2020, ISBN 978-3-88579-700-5,
[Conference or Workshop Item]

Abstract

The security of the commonly used face recognition algorithms is often doubted, as they appear vulnerable to so-called presentation attacks. While there are a number of detection methods that are using different light spectra to detect these attacks this is the first work to explore skin properties using the ultraviolet spectrum. Our multi-sensor approach consists of learning features that appear in the comparison of two images, one in the visible and one in the ultraviolet spectrum. We use brightness and keypoints as features for training, experimenting with different learning strategies. We present the results of our evaluation on our novel Face UV PAD database. The results of our method are evaluated in an leave-one-out comparison, where we achieved an APCER/BPCER of 0%/0.2%. The results obtained indicate that UV images in presentation attack detection include useful information that are not easy to overcome.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Siegmund, Dirk ; Kerckhoff, Florian ; Yeste Magdaleno, Javier ; Jansen, Nils ; Kirchbuchner, Florian ; Kuijper, Arjan
Title: Face Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Features
Language: English
Abstract:

The security of the commonly used face recognition algorithms is often doubted, as they appear vulnerable to so-called presentation attacks. While there are a number of detection methods that are using different light spectra to detect these attacks this is the first work to explore skin properties using the ultraviolet spectrum. Our multi-sensor approach consists of learning features that appear in the comparison of two images, one in the visible and one in the ultraviolet spectrum. We use brightness and keypoints as features for training, experimenting with different learning strategies. We present the results of our evaluation on our novel Face UV PAD database. The results of our method are evaluated in an leave-one-out comparison, where we achieved an APCER/BPCER of 0%/0.2%. The results obtained indicate that UV images in presentation attack detection include useful information that are not easy to overcome.

Title of Book: BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group
Publisher: Gesellschaft für Informatik
ISBN: 978-3-88579-700-5
Uncontrolled Keywords: Biometric identification systems, Spoofing attacks, Biometrics, Security technologies
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 19th International Conference of the Biometrics Special Interest Group
Event Location: virtual Conference
Event Dates: 16.-18.09.2020
Date Deposited: 09 Apr 2021 10:03
Official URL: https://dl.gi.de/handle/20.500.12116/34329
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