Presentation Attack Detection for Smartphone Based Fingerphoto Recognition Using Second Order Local Structures
Pankaj Wasnik, Raghavendra Ramachandra, Kiran Bylappa Raja, Christoph Busch · 2018
Fingerprint recognition on smartphone provides a good alternative over traditional security measures such as lock-patterns and pin. However, such fingerprint systems have some inherent problems such as the fact that user will leave their latent fingerprint on the sensor, and the limited sensor area. Additionally, fingerprint sensors impact on the cost and form factor of the device. Hence, in literature, the camera based approaches such as fingerphoto recognition systems got the attention of many researchers and manufacturers. However, such systems are highly vulnerable to presentation attacks such as photo-prints, display and replay attacks. To countermeasure these attacks, we propose a robust presentation attack detection scheme based on the features extracted from the maximum response images obtained from the convolution of second order Gaussian derivatives and the input images at multiple scales. The proposed scheme has achieved the detection performance of BPCER of 1.8%, 0.0% and 0.66% at APCER=10% for the presentation attack instrument species i.e., print-photo, display and replay attacks respectively.