Zhiming Liu and Chengjun Liu, IEEE

A Hybrid Color and Frequency Features

Methodfor Face Recognition

Introduction

Algorithms and procedures

Experiments

Conclusion

Outline

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.

Introduction

Introduction

RIQ : R of the RGB + IQ of the YIQ

Algorithms and procedures

Initial image

R, I, Q

Real part

Discrete Fourier transform of a face image

Imaginary part

Magnitude Mask

Algorithms and procedures

Algorithms and procedures

Algorithms and procedures

Algorithms and procedures

EFM method:PCA reduce dimensionalityFLD separated pattern classes

PCA: Let

……..(1) (m<N)

X :a random vector representing a frequency pattern vector.

: are the eigenvectors largest eigenvalues of X

Algorithms and procedures

Algorithms and procedures

Algorithms and procedures

FLD:

S(w) : within-class scatter matrixS(b) : between-class scatter matrix,

)( )(

)(

w

b

SStrJ

Algorithms and procedures

Algorithms and procedures

Algorithms and procedures

Database: FRGC version 2 Experiment 4

the Training set contains 12 776 images that are either controlled or uncontrolled.

Experiments

Experiments

Experiments

Experiments

0.9 0.55 0.95

Experiments

Experiments

Experiments

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.

Conclusion

Thanks for your attention !!!