Multi-bits biometric string generation based on the likelyhood ratio

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)

Binary Biometrics: An Analytic Framework to Estimate the Bit Error Probability under Gaussian Assumption

In recent years the protection of biometric data has gained increased interest from the scientific community. Methods such as the helper data system, fuzzy extractors, fuzzy vault and cancellable biometrics have been proposed for protecting biometric data. Most of these methods use cryptographic primitives and require a binary representation from the real-valued biometric data. Hence, the similarity of biometric samples is measured in terms of the Hamming distance between the binary vector obtained at the enrolment and verification phase. The number of errors depends on the expected error probability Pe of each bit between two biometric samples of the same subject. In this paper we introduce a framework for analytically estimating Pe under the assumption that the within-and between-class distribution can be modeled by a Gaussian distribution. We present the analytic expression of Pe as a function of the number of samples used at the enrolment (Ne) and verification (Nv) phases. The analytic expressions are validated using the FRGC v2 and FVC2000 biometric databases

Towards a more secure border control with 3D face recognition

Biometric data have been integrated in all ICAO compliant passports, since the ICAO members started to implement the ePassport standard. The additional use of three-dimensional models promises significant performance enhancements for border control points. By combining the geometry- and texture-channel information of the face, 3D face recognition systems show an improved robustness while processing variations in poses and problematic lighting conditions when taking the photo. This even holds in a hybrid scenario, when a 3D face scan is compared to a 2D reference image. To assess the potential of three-dimensional face recognition, the 3D Face project was initiated. This paper outlines the approach and research results of this project: The objective was not only to increase the recognition rate but also to develop a new, fake resistant capture device. In addition, methods for protection of the biometric template were researched and the second generation of the international standard ISO/IEC 19794-5:2011 was inspired by the project results

A flexible hierarchical piecewise linear simulator

In this paper, a piecewise linear (PL) simulator, called PLANET, will be presented. New features in contrast to other existing (piecewise linear) simulators are a flexible hierarchical data structure which retains the hierarchy in the simulated system, and the use of a simplified form of the Katzenelson algorithm to solve the circuit equations. Owing to the PL-concept, the simulator is capable of performing full mixed-level and mixed-mode simulations. Due to the new concept, the hierarchically organized simulator can be used by advantage in a hierarchical design environment. The replacement of a single component by a subcircuit becomes facile. The hierarchical representation of a circuit or system makes it easy to exploit latency in a circuit by means of numerical integration techniques having variable stepsize or by employing an event-driven approach

A comparison of piecewise linear model descriptions

Current methods for storing piecewise-linear mappings are discussed and compared. To do so, the model descriptions are all transformed into a general form. Among the aspects compared are the ease of modeling, the class of functions that can be modeled using a certain model description, and the suitability of using the models in simulators. No best model description is found, but it is made apparent that some models are better suited for certain applications than other