DocumentCode :
3082473
Title :
Information theoretic capacity analysis for biometric hashing methods
Author :
Karabat, Cagatay ; Erdogan, Hakan ; Mihcak, Mehmet Kivanc
Author_Institution :
TUBITAK Centre of Res. for Adv. Technol. of Inf. & Inf. Security, TUBITAK BILGEM, Gebze, Turkey
fYear :
2011
fDate :
6-8 July 2011
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we address capacity analysis of biometric hashing methods. We propose an information theoretic capacity analysis framework for biometric hashing methods by taking into account their noise resilience which is analogous to the variations of the inputs for same user. To validate the proposed framework, we make simulations with various biometric hashing methods proposed in the literature on three different face image databases. We experimentally estimate the number of different users that a biometric hashing system can accommodate by assuming that every biometric hash vector is possible to be chosen for biometric template and within-class variations can be considered as noise and each bit position has the same probabilities. Besides, we calculate equal error rate performances of the biometric hashing methods and compare them with the proposed capacity analysis framework.
Keywords :
biometrics (access control); cryptography; error statistics; face recognition; vectors; biometric hash vector; biometric hashing methods; biometric hashing system; biometric template; equal error rate performances; face image databases; information theoretic capacity analysis; noise resilience; within-class variations; Biomedical imaging; Databases; Discrete wavelet transforms; Face; Information theory; Noise; Noise measurement; biometric hash; capacity; metric;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing (DSP), 2011 17th International Conference on
Conference_Location :
Corfu
ISSN :
Pending
Print_ISBN :
978-1-4577-0273-0
Type :
conf
DOI :
10.1109/ICDSP.2011.6004919
Filename :
6004919
Link To Document :
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