Is physics-based liveness detection truly possible with a single image?

Jiamin Bai, Tian Tsong Ng, Xinting Gao, Yun-Qing Shi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

75 Scopus citations

Abstract

Face recognition is an increasingly popular method for user authentication. However, face recognition is susceptible to playback attacks. Therefore, a reliable way to detect malicious attacks is crucial to the robustness of the system. We propose and validate a novel physics-based method to detect images recaptured from printed material using only a single image. Micro-textures present in printed paper manifest themselves in the specular component of the image. Features extracted from this component allows a linear SVM classifier to achieve 2.2% False Acceptance Rate and 13% False Rejection Rate (6.7% Equal Error Rate). We also show that the classifier can be generalizable to contrast enhanced recaptured images and LCD screen recaptured images without re-training, demonstrating the robustness of our approach.

Original languageEnglish (US)
Title of host publicationISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems
Subtitle of host publicationNano-Bio Circuit Fabrics and Systems
Pages3425-3428
Number of pages4
DOIs
StatePublished - Aug 31 2010
Event2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010 - Paris, France
Duration: May 30 2010Jun 2 2010

Publication series

NameISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems

Other

Other2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010
CountryFrance
CityParis
Period5/30/106/2/10

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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