DocumentCode :
595213
Title :
Non-parametric score normalization for biometric verification systems
Author :
Struc, Vitomir ; Gros, J.Z. ; Pavesic, N.
Author_Institution :
Fac. of Electr. Eng., Univ. of Ljubljana, Ljubljana, Slovenia
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
2395
Lastpage :
2399
Abstract :
In this paper we study the problem of score normalization in biometric verification systems. Specifically, we introduce a new class of normalization techniques, which unlike the commonly used parametric score normalization techniques, such as z- or t-norm, make no assumptions regarding the shape of the underlying score distribution. The proposed class of normalization techniques first estimates the relevant score distribution in an impostor-centric manner using kernel density estimation and then maps the estimated distribution to a common one. Our experimental results obtained on the FRGCv2 face database show that the proposed non-parametric score normalization techniques consistently outperform their parametric counterparts when the target distribution takes a log-normal form and that all assessed techniques, i.e., z-, t-, zt- and tz-norms, improve upon the setting where no score normalization is used.
Keywords :
biometrics (access control); estimation theory; visual databases; FRGCv2 face database; biometric verification systems; impostor-centric manner; kernel density estimation; log-normal form; nonparametric score normalization; parametric score normalization techniques; score distribution; target distribution; Databases; Face; Frequency estimation; Kernel; Probability density function; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460648
Link To Document :
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