Face Recognition Based on Wavelet Transform and Image Principle Component Analysis

Author

Jun, Yang ; Hong-Zhao, Yuan ; Xiu-Qiong, Zhang ; Zhi-Sheng, Gao

Author_Institution

Coll. of Comput. Sci., Sichuan Normal Univ., Chengdu

fYear

2008

fDate

20-22 Dec. 2008

Firstpage

354

Lastpage

357

Abstract

Image principle component analysis (IMPCA) is a rapid direct feature extract approach from matrix. We present the basic theory of IMPCA from the view of minimizing the mean reconstruction error. We analyze the feature generated from IMPCA and find they present row characters. Wavelet transform can be used in reducing noise of images and the wavelet image should be more suitable for recognition. Our proposed method firstly transforms face image with wavelet and gets coefficients of different frequency, then horizontal detail coefficient is enhanced. The image generated by wavelet inverse transform is as new object and is recognized using IMPCA. The experiment result on ORL face database presents the proposed method is efficient and the recognition accuracy rate is better than IMPCA only.

Keywords

face recognition; feature extraction; image denoising; image reconstruction; principal component analysis; wavelet transforms; face recognition; horizontal detail coefficient; image noise reduction; image principle component analysis; mean reconstruction error; rapid direct feature extract approach; wavelet image; wavelet transform; Character generation; Error analysis; Face recognition; Feature extraction; Image analysis; Image recognition; Image reconstruction; Noise reduction; Wavelet analysis; Wavelet transforms; face recognition; image principle component analysis (IMPCA); wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Electrical Engineering, 2008. ICCEE 2008. International Conference on

Conference_Location

Phuket

Print_ISBN

978-0-7695-3504-3

Type

conf

DOI

10.1109/ICCEE.2008.34

Filename

4741006