DocumentCode :
939640
Title :
“Whitenedfaces” Recognition With PCA and ICA
Author :
Liao, Ling-Zhi ; Luo, Si-Wei ; Tian, Mei
Volume :
14
Issue :
12
fYear :
2007
Firstpage :
1008
Lastpage :
1011
Abstract :
This letter develops a simple and effective whitening method for flattening the power-law power spectrum of face images and combines the whitening technique and PCA/ICA for face recognition. The whitening parameter in the whitening filter is adaptive to the input data so as to make the power spectrum of the whitened results as flat as possible. This proposed method is computationally saving for using fast Fourier transform algorithms. The transformed ldquowhitenedfacesrdquo are applied to face recognition with PCA and ICA coding strategies, respectively. The results show that the whitening processing will bring better recognition performances for both PCA and ICA representations.
Keywords :
face recognition; fast Fourier transforms; independent component analysis; principal component analysis; fast Fourier transform algorithm; independent component analysis; power-law power face image spectrum; principal component analysis; whitenedface recognition; Face recognition; independent component analysis (ICA); power spectrum; principle component analysis (PCA); whitening;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2007.904704
Filename :
4358011
Link To Document :
بازگشت