1 April 2000 Human face recognition using PCA on wavelet subband
Author Affiliations +
J. of Electronic Imaging, 9(2), (2000). doi:10.1117/1.482742
Abstract
Together with the growing interest in the development of human and computer interface and biometric identification, human face recognition has become an active research area since early 1990. Nowadays, principal component analysis (PCA) has been widely adopted as the most promising face recognition algorithm. Yet still, traditional PCA approach has its limitations: poor discriminatory power and large computational load. In view of these limitations, this article proposed a subband approach in using PCA— apply PCA on wavelet subband. Traditionally, to represent the human face, PCA is performed on the whole facial image. In the proposed method, wavelet transform is used to decompose an image into different frequency subbands, and a midrange frequency subband is used for PCA representation. In comparison with the traditional use of PCA, the proposed method gives better recognition accuracy and discriminatory power; further, the proposed method reduces the computational load significantly when the image database is large, with more than 256 training images. This article details the design and implementation of the proposed method, and presents the encouraging experimental results.
G. C. Feng, P. C. Yuen, D. Q. Dai, "Human face recognition using PCA on wavelet subband," Journal of Electronic Imaging 9(2), (1 April 2000). http://dx.doi.org/10.1117/1.482742
JOURNAL ARTICLE
8 PAGES


SHARE
KEYWORDS
Principal component analysis

Facial recognition systems

Wavelets

Databases

Image resolution

Wavelet transforms

Computing systems

RELATED CONTENT

Space solar EUV and x-ray imaging camera
Proceedings of SPIE (October 13 2008)
Immune algorithm for KDD
Proceedings of SPIE (September 25 2001)
Technology options for imaging spectrometry
Proceedings of SPIE (November 15 2000)
PACS according to Murphy what can and will go...
Proceedings of SPIE (May 16 2002)

Back to Top