Face recognition based on Gabor features

Author

Bui, Len ; Tran, Dat ; Huang, Xu ; Chetty, Girija

Author_Institution

Fac. of Inf. Sci. & Eng., Univ. of Canberra, Canberra, ACT, Australia

fYear

2011

fDate

4-6 July 2011

Firstpage

264

Lastpage

268

Abstract

The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates.

Keywords

Gabor filters; face recognition; feature extraction; principal component analysis; support vector machines; visual databases; AT&T database; AdaBoost algorithm; FERET database; Gabor features; Gabor filters; PCA; SVM; discriminative method; face recognition; feature vector extraction; meta-algorithm; principal component analysis; public face database; support vector machine; Face; Face recognition; Feature extraction; Kernel; Principal component analysis; Support vector machines; Training; AdaBoost; Gabor feature; Principal Component Analysis; Support Vector Machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Visual Information Processing (EUVIP), 2011 3rd European Workshop on

Conference_Location

Paris

Print_ISBN

978-1-4577-0072-9

Type

conf

DOI

10.1109/EuVIP.2011.6045542

Filename

6045542