On the effectiveness of local binary patterns in face anti-spoofing

Idiap Research Institute

Abstract

Abstract—Spoofing attacks are one of the security traits that biometric recognition systems are proven to be vulnerable to. When spoofed, a biometric recognition system is bypassed by presenting a copy of the biometric evidence of a valid user. Among all biometric modalities, spoofing a face recognition system is particularly easy to perform: all that is needed is a simple photograph of the user. In this paper, we address the problem of detecting face spoofing attacks. In particular, we inspect the potential of texture features based on Local Binary Patterns (LBP) and their variations on three types of attacks: printed photographs, and photos and videos displayed on electronic screens of different sizes. For…

Citation impact

697
total citations
FWCI
16.59
Percentile
100%
References
19
Citations per year

Authors

3

Topics & keywords

Keywords
  • Spoofing attack
  • Biometrics
  • Computer science
  • Local binary patterns
  • Face (sociological concept)
  • Facial recognition system
  • Artificial intelligence
  • Set (abstract data type)
UN Sustainable Development Goals
  • Reduced inequalities
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Funding