A weighted pseudo-Zernike feature for face recognition

Author

Alirezaee, Shahpour ; Ahmadi, Majid ; Aghaeinia, Hassan ; Rashidzadeh, Rashid

Author_Institution

Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran

fYear

2005

fDate

1-4 May 2005

Firstpage

1914

Lastpage

1917

Abstract

Pseudo-Zernike polynomials are well known and widely used in the analysis of optical systems. In this paper, we introduce a weighted pseudo-Zernike feature for face recognition. The EA strategy is used to maximize the Fisher linear discriminant function (FLD) over the Pseudo-Zernike moments. The argument, which maximizes the FLD criteria, is selected as the proposed weight function. To evaluate the performance of the proposed feature, experimental studies are carried out on the ORL database images of Cambridge University. The numerical results show 97.75% recognition rate on the ORL database with the weighted pseudo-Zernike feature (with order 10) and 65, 146,40 neurons for the input, hidden, and output layers while this amount for the original pseudo-Zernike is 96.5%

Keywords

Zernike polynomials; face recognition; Fisher linear discriminant function; database images; face recognition; optical systems; weighted pseudo-Zernike polynomials; Face detection; Face recognition; Feature extraction; Image databases; Image recognition; Neurons; Optical noise; Pattern recognition; Polynomials; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2005. Canadian Conference on

Conference_Location

Saskatoon, Sask.

ISSN

0840-7789

Print_ISBN

0-7803-8885-2

Type

conf

DOI

10.1109/CCECE.2005.1557356

Filename

1557356