Abstract

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.

Highlights

  • Biometric application refers to the automated recognition of individuals based on their physiological and/or behavioural characteristics (Jain et al, 2004)

  • The results show 0 value for the mean, standard deviation, skewness and kurtosis of the image and one polarization (Ipol) for the three materials under near infrared (NIR) light

  • Because of the 0 value, the Ipol images under NIR light have been omitted from further analysis

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Summary

Introduction

Biometric application refers to the automated recognition of individuals based on their physiological and/or behavioural characteristics (Jain et al, 2004). Due to the high demand on these biometric applications, fingerprint, face and iris have been the three most popular and mature modalities among the others (Jain et al, 2004). Face spoofing is an attack where photograph, video or mask of a valid user is presented in front of face recognition system as trial to gain access. Face Recognition (FR) systems are vulnerable to spoofing attacks (Kose and Dugelay, 2013a). An imposter can obtain a photo of an authorized person, plays a video, or display a 3D model such as a face mask which mimics a valid individual, in front of the sensor to gain access (Pan et al, 2008)

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