Face recognition approach based on 2D discrete fractional Fourier transform

Author

Liu, Bowen ; Wang, Feng

Author_Institution

Sch. of Comput. Sci. & Technol., Beijing Inst. of Technol., Beijing, China

fYear

2011

fDate

27-29 May 2011

Firstpage

656

Lastpage

660

Abstract

The fractional Fourier transform (FRFT) has the mixed time and frequency characteristics of signals. And FRFT is a powerful and effective tool for time-varying and nonstationary signal processing. To address face recognition problem, an approach based on 2D discrete fractional Fourier transform (2D-DFRFT) is proposed in this paper. First of all, the 2D-DFRFT of a facial image is computed. Then Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA) are combined to perform discriminative feature extraction. Then the nearest neighbor (NN) classifier is applied to perform face recognition, based on Euclidean distance. Experimental results on ORL face database indicate that the proposed approach obtains good recognition effects.

Keywords

discrete Fourier transforms; face recognition; image classification; principal component analysis; visual databases; 2D discrete fractional Fourier transform; 2D-DFRFT; Euclidean distance; Fisher linear discriminant analysis; ORL face database; discriminative feature extraction; face recognition problem; facial image; nearest neighbor classifier; nonstationary signal processing; principal component analysis; Databases; Equations; Face; Face recognition; Optical imaging; Principal component analysis; Face recognition; Fisher Linear Discriminant Analysis (FLDA); Fractional Fourier Transform (FRFT); Principal Component Analysis (PCA);

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-61284-485-5

Type

conf

DOI

10.1109/ICCSN.2011.6014352

Filename

6014352