Human face recognition using PCA on wavelet subband

Citation
Gc. Feng et al., Human face recognition using PCA on wavelet subband, J ELECTR IM, 9(2), 2000, pp. 226-233
Citations number
35
Categorie Soggetti
Optics & Acoustics
Journal title
JOURNAL OF ELECTRONIC IMAGING
ISSN journal
10179909 → ACNP
Volume
9
Issue
2
Year of publication
2000
Pages
226 - 233
Database
ISI
SICI code
1017-9909(200004)9:2<226:HFRUPO>2.0.ZU;2-D
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 ana lysis (PCA) has been widely adopted as the most promising face recognition algorithm. Yet still. traditional PCA approach has its limitations: poor di scriminatory power and large computational load. In view of these limitatio ns. this article proposed a subband approach in using PCA-apply PCA on wave let subband. Traditionally, to represent the human face, PGA is performed o n the whole facial image. In the proposed method, wavelet transform is used to decompose an image into different frequency subbands, and a midrange fr equency subband is used for PCA representation. In comparison with the trad itional use of PCA, the proposed method gives better recognition accuracy a nd discriminatory power; further the proposed method reduces the computatio nal bad 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. (C) 200 0 SPIE and IS&T. [S1017-9909(00)01702-5].