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실시간 영상처리를 이용한 얼굴 인증 시스템 구현

The Implementation of Face Authentication System Using Real-Time Image Processing

  • 백영현 (원광대학교 전기전자 및 정보공학부) ;
  • 신성 (원광대학교 전기전자 및 정보공학부) ;
  • 문성룡 (원광대학교 전기전자 및 정보공학부)
  • 발행 : 2008.04.25

초록

본 논문은 실시간 영상처리 기반의 얼굴 인증시스템 구현을 제안하였다. 실시간 얼굴 인증 시스템 구현을 위해 두 단계의 처리과정을 수행한다. 첫 번째 얼굴검출 단계에서 Wavelet 변환, LoG 연산자, Hausdorff 거리 매칭 알고리즘의 특징을 사용하여 최적화된 얼굴 검출한다. 두 번째 단계에서 실시간 얼굴 인식을 위해 적용한 새로운 dual-line 주성분분석법은 일반적인 주성분분석법의 국부적인 변화를 수용할 수 있도록 수직라인에 수평라인을 결합하여 제안하였다. 제안된 시스템은 크기나 해상도에 영향을 적게 받으며, 모의실험 결과 기존 알고리즘보다 더 우수함을 보였다. 마지막으로 얼굴 인증시스템의 구현을 통하여 성능검증 및 실시간으로 처리됨을 확인하였다.

In this paper, it is proposed the implementation of face authentication system based on real-time image processing. We described the process implementing the two steps for real-time face authentication system. At first face detection steps, we describe the face detection by using feature of wavelet transform, LoG operator and hausdorff distance matching. In the second step we describe the new dual-line principal component analysis(PCA) for real-time face recognition. It is combines horizontal line to vertical line so as to accept local changes of PCA. The proposed system is affected a little by the video size and resolution. And then simulation results confirm the effectiveness of out system and demonstrate its superiority to other conventional algorithm. Finally, the possibility of performance evaluation and real-time processing was confirmed through the implementation of face authentication system.

키워드

참고문헌

  1. M. H. Yang, D. J. Kriegman, N. Ahuja "Detecting Face in Image : A Survey," IEEE Trans. Pattern Analysys and Machine Intelligence, Vol. 24, No. 1, pp. 34-58, 2002 https://doi.org/10.1109/34.982883
  2. Sirovichm L. and Kirby, M., "Low-dimensional procedure for the characterization of human faces," J. Optical Soc. Amer., Vol. 4, pp. 519-524, 1987 https://doi.org/10.1364/JOSAA.4.000519
  3. Kirby, M. and Sirovich, L.,"Application of the KL Procedure for the Characterization of Human Face," IEEE Trans. Pattern Analysys and Machine Intelligence, Vol. 12, No. 1, pp. 103-108, 1990 https://doi.org/10.1109/34.41390
  4. Turk, M, and Pentland, A., "Eigenfaces for Recognition," J. Cognitive Neuroscience, Vol. 3, No. 1, pp. 71-86, 1991 https://doi.org/10.1162/jocn.1991.3.1.71
  5. R. Crane, "A simplified approach to Image Processing," Prentice-Hall, 1997
  6. D. Chai, "Face segmentation using skin-color map in videophone applications," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 83, No. 5, pp. 705-740, 1999
  7. O. K. Kwon, D. G. Sim, R. H. Park, "Object Matching Algorithm Using Robust Hausdorff Distance Measure," IEEE Trans., Vol. 8, No. 3, pp. 1057-7149, March, 1999
  8. Hertog Nugroho, Shinji Ozawa, "Tracking Multiple Moving Objects form Monocular Image Sequences with Hausdorff Distance and Context Information," T.IEE Japan, Vol. 118-121, No. 7/8, pp. 1138-1149, 1998
  9. Y. H. Baek, "A Study on Color Image Edge Detection using Adaptive Morphological Wavelet-CNN Algorithm" Wonkwang University, M. S.,Feb.2002
  10. Kwang In Kim, Keechul Jung and Hang Joon Kim, "Face Recognition Using Kernel Principal Component Analysis", IEEE Signal proc. Vol.9, No.2, pp.40-42, Feb. 2002 https://doi.org/10.1109/97.991133
  11. Y. J. Song, "A Performance Analysis of the Face Recognition Based on PCA/LDA on Distance Measures" The Korean Academic Industrial Society, Vol. 6, No. 3, pp. 249-254, 2005
  12. Bernhard Scholkopf and Alexander Smola, "Nonlinear component analysis as a kernel eigenvalue problem," Neural Computation, Vol. 10, No. 5, pp. 1299-1319, 1998 https://doi.org/10.1162/089976698300017467
  13. Andy Hopper FREng, "The ORL face database", AT&T(Olivetti) Research Laboratory Cambridge
  14. P. Halinan, A. Yuille and D. Mumford, "Harvard face database", Harvard University