A Hybrid Color and Frequency Features Method for Face Recognition

1. A Hybrid Color and Frequency Features Methodfor Face Recognition Zhiming Liu and Chengjun Liu, IEEE

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

3. Introduction • Uncontrolled illumination • Color information and frequency features derived by means of the Discrete Fourier Transform (DFT) help improve face recognition performance. • This correspondence presents a novel hybrid Color and Frequency Features (CFF) method for face recognition.

4. Introduction • RIQ : R of the RGB +IQ of the YIQ

5. Algorithms and procedures

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

7. Algorithms and procedures

8. Algorithms and procedures

9. Algorithms and procedures

10. 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: Let ……..(1) (m<N)

11. Algorithms and procedures

12. Algorithms and procedures

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

14. Algorithms and procedures

15. Algorithms and procedures

16. Experiments • Database: FRGC version 2 Experiment 4 • the Training set contains 12 776 images that are either controlled or uncontrolled.

17. Experiments

18. Experiments

19. Experiments

20. 0.9 0.55 0.95 Experiments

21. Experiments

22. Experiments

23. Conclusion • Future research will consider applying kernel methods, such as the multiclass Kernel Fisher Analysis (KFA) method presented in [9], to replace the EFM method for improving face recognition performance. • The hybrid color space improves face recognition performance.

24. Thanks for your attention !!!