Combined Face Recognition Using Wavelet Transform and Bayesian

Author

Liping, Niu ; Yanbin, Zheng ; Yuqiang, Dou ; XinYuan, Li

Author_Institution

Coll. of Comput. & Inf. Technol., Henan Normal Univ., Xinxiang, China

Volume

2

fYear

2009

fDate

21-22 May 2009

Firstpage

337

Lastpage

340

Abstract

A novel Bayesian approach to face recognition based on wavelet transform is proposed. The original image is decomposed into low frequency and high frequency sub-band images by applying wavelet transform, the 2DPCA algorithm is used to compute the eigenvector space of the face. Firstly Bayesian approach is used to the low frequency sub-band, select the top 10 candidate images for matching in the post processing stage, secondly Bayesian recognition is parallel processed using these high frequency sub-band images. The face recognition result was gained through weigh-adding arraying. Its efficiency and superiority are clarified by comparative experiment on a subset of FERET face data.

Keywords

Bayes methods; eigenvalues and eigenfunctions; face recognition; image matching; parallel processing; principal component analysis; wavelet transforms; 2DPCA algorithm; Bayesian approach; eigenvector space; face recognition; image matching; parallel processing; principal component analysis; wavelet transform; Bayesian methods; Covariance matrix; Discrete wavelet transforms; Face recognition; Feature extraction; Frequency; Image databases; Image recognition; Principal component analysis; Wavelet transforms; 2DPCA; Bayesian theory; Face recognition; Wavelet Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Computing Science, 2009. ICIC '09. Second International Conference on

Conference_Location

Manchester

Print_ISBN

978-0-7695-3634-7

Type

conf

DOI

10.1109/ICIC.2009.196

Filename

5169080