Passive imaging at 250 GHz for detection of face presentation attacks

Face presentation attacks are becoming more efficient since new 3D facial masks are used. Passive terahertz imaging offers specific physical properties that may improve presentation attack detection capabilities. The non-zero transmission capability through a variety of non-metallic materials may provide necessary information for presentation attack detection. The aim of this paper is to present outcomes of a study on face presentation attack detection using passive imaging at 250 GHz. An analysis of presentation attacks for facial recognition systems using custom displayed and printed photographs, 3D-printed and full-face flexible 3D-latex masks, is provided together with spectral characterization of various presentation attack instruments. A set of experiments with various instruments and various sets of clothing is described and discussed. Finally, two presentation attack detection methods are proposed. The first method is based on a threshold corresponding to a difference between mean intensities of selected regions of interests while the second method uses eight different deep learning classifiers to detect presentation attacks. Results of two validation schemes are presented.