Dynamic Fingerprint Statistics: Application in Presentation Attack Detection

Fingerprint recognition systems have proven significant performance in many services such as forensics, border control, and mobile applications. Even though fingerprint systems have shown high accuracy and user acceptance, concerns have raised questions about the possibility of having our fingerprin...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.95594-95604
Main Authors: Husseis, Anas, Liu-Jimenez, Judith, Goicoechea-Telleria, Ines, Sanchez-Reillo, Raul
Format: Article
Language:English
Subjects:
Applications programs
Biometric recognition systems
Feature extraction
Fingerprint
Fingerprint verification
Heuristic algorithms
Mobile computing
Nonlinear distortion
Optical distortion
Optical imaging
Optical measuring instruments
Optical sensors
presentation attack
presentation attack detection
spoofing
Subsystems
Support vector machines
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Summary:Fingerprint recognition systems have proven significant performance in many services such as forensics, border control, and mobile applications. Even though fingerprint systems have shown high accuracy and user acceptance, concerns have raised questions about the possibility of having our fingerprint pattern stolen and presented to the system by an imposter. In this paper, we propose a dynamic presentation attack detection mechanism that seeks to mitigate presentation attacks. The adopted mechanism extracts the variation of global fingerprint features in video acquisition scenario and uses it to distinguish bona fide from attack presentations. For that purpose, a dynamic dataset has been collected from 11 independent subjects, 6 fingerprints per user, using thermal and optical sensors. A total of 792 bona fide presentations and 2772 attack presentations are collected. The final PAD subsystem is evaluated based on the standard ISO/IEC 30107-3. Considering SVM classification and 3 folds cross validation, the obtained error rates at 5% APCER are 18.1% BPCER for the thermal subset and 19.5% BPCER for the optical subset.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2995829