Title :
Arbitrary illumination conditions for facial identification
Author :
Travieso, Carlos M. ; Alonso, Jesús B. ; Ferrer, Miguel A.
Author_Institution :
Univ. de Las Palmas de Gran Canaria, Las Palmas
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 and Yale Databases. We have used as parameterisation different transformed dominions by James L. Wyman, et al. (2002), and a support vector machine (SVM) by Anil K. Jain, et al. (2004) as classifier. This system has been adjusted with our experiments for obtaining an 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; support vector machines; biometric system; facial identification; illumination condition; parameterisation different transformed dominion; support vector machine; Biometrics; Face detection; Face recognition; Image databases; Lighting; Neural networks; Principal component analysis; Robustness; Support vector machine classification; Support vector machines; Biometric identification; classification system; facial recognition; neural network (NN); support vector machines (SVM);
Conference_Titel :
Security Technology, 2007 41st Annual IEEE International Carnahan Conference on
Conference_Location :
Ottawa, Ont.
Print_ISBN :
978-1-4244-1129-0
DOI :
10.1109/CCST.2007.4373474
