Journal of KIISE (정보과학회 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
권호 표지
DOI QR코드

DOI QR Code

Video Based Face Spoofing Detection Using Fourier Transform and Dense-SIFT

푸리에 변환과 Dense-SIFT를 이용한 비디오 기반 Face Spoofing 검출

  • 한호택 (서강대학교 컴퓨터공학과) ;
  • 박운상 (서강대학교 컴퓨터공학과)
  • Received : 2014.12.10
  • Accepted : 2015.02.02
  • Published : 2015.04.15
⟨ Previous Next ⟩

Abstract

Security systems that use face recognition are vulnerable to spoofing attacks where unauthorized individuals use a photo or video of authorized users. In this work, we propose a method to detect a face spoofing attack with a video of an authorized person. The proposed method uses three sequential frames in the video to extract features by using Fourier Transform and Dense-SIFT filter. Then, classification is completed with a Support Vector Machine (SVM). Experimental results with a database of 200 valid and 200 spoof video clips showed 99% detection accuracy. The proposed method uses simplified features that require fewer memory and computational overhead while showing a high spoofing detection accuracy.

얼굴 인식기반의 사용자 보안 시스템은 접근이 허가된 사용자의 사진이나 비디오를 이용한 공격에 취약하다는 단점을 가지고 있다. 본 연구에서는 인증되지 않은 사용자가 비디오를 이용하여 시스템에 접근할 경우 해당 공격 시도를 검출하기 위한 위변조(Spoof) 검출 방법을 제안한다. 제안하는 방법은 연속된 3개의 Frame에서 푸리에 변환과 Dense-SIFT 구분자를 사용하여 400개의 실제 및 위변조 비디오 영상을 대상으로 실험한 결과 99%의 검출 정확도를 보였다.

Keywords

Acknowledgement

Supported by : 한국연구재단

References

  1. A. K. Jain and A. Ross, Handbook of Biometrics, pp. 1-22. Springer, 2008.
  2. K. A. Nixon, V. Aimale and R. K. Rowe, Handbook of Biometrics, pp. 403-423, Springer, 2008.
  3. C. Rathgeb and A. Uhl, "Statistical Attack Against Iris-Biometric Fuzzy Commitment Schemes," Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 23-30, 2011.
  4. A. d. S. Pinto, H. Pedrini, W. R. Schwartz and A. Rocha, "Video-Based Face Spoofing Detection through Visual Rhythm Analysis," Proc. of the 25th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 221-228, 2012.
  5. J. Li, Y. Wang, T. Tan, and A. K. Jain, "Live Face Detection Based on the Analysis of Fourier Spectra," Proc. of the SPIE on Biometric Technology for Human Identification, pp. 296-303, 2004.
  6. G. Pan, L. Sun, Z. Wu and S. Lao, "Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera," Proc. of the IEEE 11th International Conference on Computer Vision (ICCV), pp. 1-8, Oct. 2007.
  7. A. Anjos and S. Marcel, "Counter-Measures to Photo Attacks in Face Recognition: A Public Database and A Baseline," Proc. of the 2011 International Joint Conference on Biometrics (IJCB), pp. 1-7, 2011.
  8. D. G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110, 2004. https://doi.org/10.1023/B:VISI.0000029664.99615.94