The Design and Compilation of a Facial Spoof Database on Various Textures

Abstract

Face biometrics plays an important role in various authentication applications. However, one of the main design challenges for an accurate face biometrics is detecting spoof artificial artifacts. The development of robust anti-spoofing algorithm requires for rigorous system training and testing on facial database that includes various possible spoof specimen which reflects different variations of spoofing attacks. Currently, the databases which are used to test face anti-spoofing algorithms are limited in terms of texture variations. Therefore, in this paper, our focus is to introduce a face spoofing database which is compiled from various types of spoofing textures. Our database was collected from 30 different subjects and fake faces were recaptured on various forms which include four different types of paper-based textures and three different digital display devices. All images were collected using a high precision camera device. This database would provide a more realistic and challenging platform for facial anti-spoofing research.