Preserving the privacy of biometric information
stored in biometric systems is becoming a key issue. An
important element in privacy protecting biometric systems is
the quantizer which transforms a normal biometric template
into a binary string. In this paper, we present a user-specific quantization method based on a likelihood ratio approach (LQ).
The bits generated from every feature are concatenated to form a fixed length binary string that can be hashed to protect its privacy. Experiments are carried out on both fingerprint data (FVC2000) and face data (FRGC). Results show that our proposed quantization method achieves a reasonably good performance in terms of FAR/FRR (when FAR is 10−4, the corresponding FRR are 16.7% and 5.77% for FVC2000 and FRGC, respectively).
|Title of host publication||IEEE conference on Biometrics: Theory, Applications and Systems|
|Editors||K.W. Bowyer, P.J. Flynn, V. Govindaraju, N. Ratha|
|Place of Publication||Los Alamitos, CA, USA|
|Number of pages||6|
|Publication status||Published - 29 Sep 2007|