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Effects of Visible and Near Infrared Polarized Lights on Spoofing Face Detection

机译:可见光和近红外偏振光对欺骗人脸检测的影响

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摘要

Face spoofing countermeasure is vital to avoid an imposter from gaining access to security biometric systems by using face masks in various forms that mimic a valid user face. Recently, several studies have shown the ability of visible polarized light in distinguishing real and fake faces. In this paper, polarization imaging systems using visible and near infrared (NIR) are proposed to examine the effects on the polarization images as trial to distinguish between genuine face and spoof face presentation attacks: photo paper and iPad face display; based on the optical properties of the materials. The findings from the investigations suggest that in general, NIR light could not be used to distinguish between genuine face and photo paper under a polarization lighting condition. In contrast, the visible light provides significant difference of the Stokes images between the materials. Classification between real face and iPad display can easily be done by manipulating the polarization angle. A new feature fusion formula named as the SDOLP3F is introduced to differentiate between the real and the fake traits. The SDOLP3F results presented in this paper show the highest accuracy rate compared to the individual measures. The results illustrate the robustness of the proposed anti-spoofing algorithm based on a small sample.
机译:面部欺骗对策对于通过使用模仿有效用户面部的各种形式的面罩来避免冒名顶替者进入安全生物识别系统至关重要。最近,一些研究表明可见偏振光能够区分真实和伪造的面孔。在本文中,提出了使用可见光和近红外(NIR)的偏振成像系统来检查对偏振图像的影响,以尝试区分真实的面部和欺骗性的面部表情攻击:相纸和iPad面部显示器;基于材料的光学特性。调查的结果表明,通常,在偏振照明条件下,近红外光不能用于区分真面和相纸。相反,可见光在材料之间提供了斯托克斯图像的显着差异。通过操纵偏振角,可以很容易地完成真实面部和iPad显示器之间的分类。引入了一个新的特征融合公式,称为SDOLP3F,以区分真实特征和伪特征。与单独的措施相比,本文提出的SDOLP3F结果显示出最高的准确率。结果说明了基于小样本提出的反欺骗算法的鲁棒性。

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