Textural feature based face recognition for single training images

Author

Singh, R. ; Vatsa, M. ; Noore, A.

Author_Institution

Lane Dept. of Comput. Sci. & Electr. Eng., West Virginia Univ., Morgantown, WV, USA

Volume

41

Issue

11

fYear

2005

fDate

5/26/2005 12:00:00 AM

Firstpage

640

Lastpage

641

Abstract

A novel face recognition algorithm using single training face image is proposed. The algorithm is based on textural features extracted using the 2D log Gabor wavelet. These features are encoded into a binary pattern to form a face template which is used for matching. Experimental results show that on the colour FERET database the accuracy of the proposed algorithm is higher than the local feature analysis (LFA) and correlation filter (CF) based face recognition algorithms even when the number of training images is reduced to one. In comparison with recent single training image based face recognition algorithms, the proposed 2D log Gabor wavelet based algorithm shows an improvement of more than 3% in accuracy.

Keywords

face recognition; feature extraction; image matching; image texture; wavelet transforms; 2D log Gabor wavelet; binary pattern; colour FERET database; correlation filter; face recognition algorithm; face template; features extraction; local feature analysis; single training face images; textural feature based face recognition;

fLanguage

English

Journal_Title

Electronics Letters

Publisher

iet

ISSN

0013-5194

Type

jour

DOI

10.1049/el:20050352

Filename

1437871