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A Hybrid Color and Frequency Features Method for Face Recognition

This report presents a novel hybrid method for face recognition that utilizes Color and Frequency Features (CFF). Building upon the Face Recognition Grand Challenge (FRGC) and Face Recognition Vendor Test (FRVT), we explore new techniques and algorithms to enhance recognition accuracy under various conditions. Our approach incorporates the Discrete Fourier Transform and Principal Component Analysis (PCA) to improve image processing, supported by empirical results demonstrating a recognition accuracy of 84%. The findings suggest that hybrid color space significantly improves performance in face recognition tasks.

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A Hybrid Color and Frequency Features Method for Face Recognition

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  1. A Hybrid Color and Frequency Features Methodfor Face Recognition 程式開發：賴博文 報告者：邱威智 ISMP 郭淑美老師實驗室 成員： 賴博文 鄭鈺勳 邱威智

  2. Outline • Introduction • Algorithms and procedures • Result • Conclusion

  3. Introduction Face Recognition Grand Challenge (FRGC) • New face recognition techniques Face Recognition Vendor Test (FRVT) 2002 results ?  FRGC P. Jonathon Phillips, et al. 2005

  4. Introduction Face Recognition Grand Challenge (FRGC) • 6 experiments: • still images : • controlled lighting and background • uncontrolled lighting and background • 3D imagery • multi-still imagery • between 3D and still images P. Jonathon Phillips, et al. 2005

  5. controlled still images 3D scans uncontrolled still images P. Jonathon Phillips, et al. 2005 Introduction

  6. Introduction • FRGC  uncontrolled illumination conditions • Eigenfaces and Fisherfaces method  X

  7. I Q Introduction Hybrid Color and Frequency Features (CFF) method • RIQ : R of the RGB + IQ of the YIQ • YIQ  NTSC color TV system • Y: luminance

  8. Introduction • R is more effective than the luminance ……Peichung Shih and Chengjun Liu, 2005

  9. Algorithms and procedures

  10. Discrete Fourier transform of a face image Imaginary part Initial image R, I, Q Real part Magnitude Mask Algorithms and procedures

  11. Algorithms and procedures

  12. Algorithms and procedures

  13. Algorithms and procedures

  14. X :a random vector representing a frequency pattern vector. : are the eigenvectors  largest eigenvalues of X Algorithms and procedures • EFM method: • PCA reduce dimensionality • FLD separated pattern classes • PCA: Y: reduced pattern vector

  15. Algorithms and procedures

  16. Algorithms and procedures

  17. Algorithms and procedures • FLD: S(w) : within-class scatter matrix S(b) : between-class scatter matrix,

  18. 0.9 0.55 0.95 Algorithms and procedures

  19. Result

  20. Our Result Training Test } 11

  21. Our Result

  22. worst } better Our Result • mRIQ: 84% • mR,mI,mQ:79%

  23. Conclusion • This correspondence presents a novel hybrid Color and Frequency Features (CFF) method for face recognition • The hybrid color space improves face recognition performance

  24. Thanks for your attention.

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