New Finger Photo Databases with Presentation Attacks and Demographics
Anudeep Vurity, Emanuela Marasco · 2023
Finger photo recognition has emerged as an alternative biometric authentication solution in smartphones, leveraging common RGB cameras to acquire images of human fingers, improving hygiene and user experience. The security of this technology is currently threatened by presentation attacks. Although being equipped with presentation attack detection modules is of critical importance for these systems, existing approaches are not robust to several challenges including unknown attacks and device diversity. The limited availability of training data to the research community has constrained progress. In this paper, we present two new databases of finger photos for developing anti-spoofing countermeasures, Mason Finger Photo Presentation Attack Detection iPhone 13 Pro 2022 (MFPAD-i-22) and Mason Finger Photo Presentation Attack Detection Google Pixel 32023 (MFPAD-G-23), containing live and spoof finger photos with associated demographics. MFPAD-i-22 was acquired from 112 subjects using the device iPhone 13 Pro, while MFPAD-G-23 from 100 individuals using Google Pixel 3. We also discuss a novel mobile App we developed in an Android environment based on a previously designed PAD fusing different color spaces. By providing these resources and insights, we encourage researchers to spend efforts to advance contactless fingerprint PAD in mobiles, for more secure and robust biometric systems.