Strategy for improving the reliability in the facial identification

Author

Travieso, Carlos M. ; Alonso, Jesus B. ; Ferrer, Mliguel A.

Author_Institution

Dpto. de Senales y Comunicaciones, Univ. de Las Palmas de Gran Canaria, Spain

fYear

2005

fDate

11-14 Oct. 2005

Firstpage

149

Lastpage

152

Abstract

This paper presents a simple, robust and novel for errors detection in biometric system which is applied to the Olivetti Research Laboratory (ORL) face database (400 images). We have used as parameterisation different transformed dominions (Travieso et al., 2004; Faundez, 2003), and a support vector machine (SVM) (Burges, 1998; Cristianini and Shawe-Taylor, 2000) as classifier. This system has been adjusted with our experiments for obtaining a false identification rate (FIR) of 0%, with a success rate of 90.8% a rejected samples rate of 9.2%.

Keywords

biometrics (access control); face recognition; feature extraction; support vector machines; visual databases; biometric system; error detection; face database; facial identification; false identification rate; parameterisation different transformed dominion; support vector machine; Biometrics; Face detection; Face recognition; Finite impulse response filter; Image databases; Laboratories; Robustness; Security; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Security Technology, 2005. CCST '05. 39th Annual 2005 International Carnahan Conference on

Print_ISBN

0-7803-9245-0

Type

conf

DOI

10.1109/CCST.2005.1594833

Filename

1594833