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Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis.

Yezeng Cheng1, Kirill V Larin

  • 1Biomedical Optics Laboratory, Biomedical Engineering Program, University of Houston, Texas 77204-4006, USA.

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Summary

Optical coherence tomography (OCT) can distinguish artificial fingerprint dummies from real skin, even when they fool commercial fingerprint readers. OCT image analysis shows potential for automatic spoofing detection in biometrics.

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Area of Science:

  • Biometrics
  • Optical Coherence Tomography
  • Materials Science

Background:

  • Fingerprint recognition is a common biometric method vulnerable to spoofing using artificial materials.
  • Current systems rely on surface topography, which can be mimicked by artificial fingerprints.

Purpose of the Study:

  • To evaluate optical coherence tomography (OCT) for distinguishing artificial fingerprint spoofing materials from real skin.
  • To assess the potential of OCT image analysis for automatic detection of fingerprint spoofing.

Main Methods:

  • Prepared artificial fingerprint dummies using household cement and liquid silicone rubber.
  • Tested dummies and real skin with a commercial fingerprint reader and an OCT system.
  • Analyzed OCT images using autocorrelation for pattern recognition.

Main Results:

  • Artificial fingerprints successfully spoofed the commercial fingerprint reader.
  • OCT imaging consistently identified the artificial materials.
  • Autocorrelation analysis of OCT images showed potential for automated recognition.

Conclusions:

  • OCT is effective in detecting artificial fingerprint spoofing materials.
  • OCT-based methods offer a promising approach for enhancing biometric security against spoofing.