Image Quality Assessment for Fake Biometric Detection: Application to Fingerprint and Face Recognition
The presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is
a significant problem in biometric authentication and that requires the development of new and efficient protection measures.
Here, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect
different types of fraudulent access attempts. The proposed system aims to enhance the security of biometric recognition
frameworks. The proposed system is tested on real time recognition from a web camera and on the publicly available dataset.
The experimental results, which were obtained on publicly available data sets of fingerprint and 2D face, show that the
proposed method is highly competitive compared with other state-of-the-art approaches and the analysis of the general image
quality of real biometric samples reveals highly valuable information which may be very efficiently used to discriminate them
from fake traits.
Index Terms- Attacks, biometrics, countermeasures, image quality assessment, security.