For applications such as airport border control, biometric technologies that can process many capture subjects quickly, efficiently, with weak supervision, and with minimal discomfort are desirable. Facial recognition is particularly appealing because it is minimally invasive yet offers relatively good recognition performance. Unfortunately, the combination of weak supervision and minimal invasiveness makes even highly accurate facial recognition systems susceptible to spoofing via presentation attacks. Thus, there is great demand for an effective and low cost system capable of rejecting such attacks.To this end we introduce PARAPH -- a novel hardware extension that exploits different measurements of light polarization to yield an image space in which presentation media are readily discernible from Bona Fide facial characteristics. The PARAPH system is inexpensive with an added cost of less than 10 US dollars. The system makes two polarization measurements in rapid succession, allowing them to be approximately pixel-aligned, with a frame rate limited by the camera, not the system. There are no moving parts above the molecular level, due to the efficient use of twisted nematic liquid crystals. We present evaluation images using three presentation attack media next to an actual face -- high quality photos on glossy and matte paper and a video of the face on an LCD. In each case, the actual face in the image generated by PARAPH is structurally discernible from the presentations, which appear either as noise (print attacks) or saturated images (replay attacks).

本文介绍了一种利用偏振光测量不同图像的新型硬件扩展，称为PARAPH，它可以有效地识别假面攻击媒体，并对该系统进行了评估。

通过分析极化假设进行演示攻击拒绝