Shape and texture based countermeasure to protect face recognition systems against mask attacks

Photographs, videos or masks can be used to spoof face recognition systems. In this paper, a countermeasure is proposed to protect face recognition systems against 3D mask attacks. The reason for the lack of studies on countermeasures against mask attacks is mainly due to the unavailability of public databases dedicated to mask attack. In this study, a 2D+3D mask attacks database is used that is prepared for a research project in which the authors are all involved. The proposed countermeasure is based on the fusion of the information extracted from both the texture and the depth images in the mask database, and provides satisfactory results to protect recognition systems against mask attacks. Another contribution of this study is that the countermeasure is integrated to the selected baseline systems for 2D and 3D face recognition, which provides to analyze the performances of the systems with/without attacks and with/without the countermeasure.