1 / 24

A Hybrid Color and Frequency Features Method for Face Recognition

A Hybrid Color and Frequency Features Method for Face Recognition. Zhiming Liu and Chengjun Liu , IEEE. Outline. Introduction Algorithms and procedures Experiments Conclusion. Introduction. Uncontrolled illumination

palti
Télécharger la présentation

A Hybrid Color and Frequency Features Method for Face Recognition

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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 !!!

More Related