Using score normalization to solve the score variation problem in face authentication

Authors:
Fei Yang;Shiguang Shan;Bingpeng Ma;Xilin Chen;Wen Gao
Affiliations:
Institute of Computing Technology, CAS, Beijing, China;Institute of Computing Technology, CAS, Beijing, China;Institute of Computing Technology, CAS, Beijing, China;Institute of Computing Technology, CAS, Beijing, China;Institute of Computing Technology, CAS, Beijing, China
Venue:
IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
Year:
2005

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Abstract

This paper investigates the score normalization technique for enhancing the performance of face authentication. We firstly discuss the thresholding approach for face authentication and put forward the “score variation” problem. Then, two possible solutions, Subject Specific Threshold (SST) and Score Normalization (SN), are discussed. But SST is obviously impractical to many face authentication applications in which only a single example face image is available for each subject. Fortunately, we have theoretically shown that, in such cases, score normalization technique may approximately approach the SST by using a uniform threshold. Experiments on both the FERET and CAS-PEAL face database have shown the effectiveness of SN for different face authentication methods including Correlation, Eigenface, and Fisherface.