Bionic Face Recognition Using Gabor Transformation

Author

He, Guanghui ; Tang, Yuanyan ; Zhang, Taiping

Author_Institution

Coll. of Comput. Sci., Chongqing Univ., Chongqing, China

fYear

2010

fDate

21-23 Oct. 2010

Firstpage

1

Lastpage

5

Abstract

In order to overcome the shortcomings of Principal Component Analysis (PCA) and bionic methods in feature extracting and dimension reduction, a method for extracting Gabor features of face images based on Gabor wavelet is presented. First, Gabor features are extracted from face images. After reduced by 2DPCA algorithm, the features are reduced further by rough set. Then the nearest classifier is trained for classification. The experiments being performed on Yale Face Database B human face image database show the method presented in this paper is superior to that of bionic recognition algorithm and PCA algorithm.

Keywords

biocybernetics; face recognition; feature extraction; pattern classification; principal component analysis; visual databases; Gabor transformation; Gabor wavelet; Yale face database; bionic face recognition; dimension reduction; feature extraction; human face image database; principal component analysis; Databases; Face; Face recognition; Feature extraction; Pattern analysis; Principal component analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition (CCPR), 2010 Chinese Conference on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-7209-3

Electronic_ISBN

978-1-4244-7210-9

Type

conf

DOI

10.1109/CCPR.2010.5659266

Filename

5659266