Biometric Quantization through Detection Rate Optimized Bit Allocation

C Chen,R N J Veldhuis,A H M Akkermans,T A M Kevenaar

doi:10.1155/2009/784834

C Chen, R N J Veldhuis + Show 2 more

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https://doi.org/10.1155/2009/784834

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Abstract

Extracting binary strings from real-valued biometric templates is a fundamental step in many biometric template protection systems, such as fuzzy commitment, fuzzy extractor, secure sketch, and helper data systems. Previous work has been focusing on the design of optimal quantization and coding for each single feature component, yet the binary string—concatenation of all coded feature components—is not optimal. In this paper, we present a detection rate optimized bit allocation (DROBA) principle, which assigns more bits to discriminative features and fewer bits to nondiscriminative features. We further propose a dynamic programming (DP) approach and a greedy search (GS) approach to achieve DROBA. Experiments of DROBA on the FVC2000 fingerprint database and the FRGC face database show good performances. As a universal method, DROBA is applicable to arbitrary biometric modalities, such as fingerprint texture, iris, signature, and face. DROBA will bring significant benefits not only to the template protection systems but also to the systems with fast matching requirements or constrained storage capability.

Highlights

The idea of extracting binary biometric strings was originally motivated by the increasing concern about biometric template protection [1]
This paper deals with the bit extraction module, for which we present a detection rate optimized bit allocation principle (DROBA) that transforms a real-valued biometric template into a fixed-length binary string
Generating binary strings from real-valued biometric measurements acts as a data compression process

Summary

Introduction

The idea of extracting binary biometric strings was originally motivated by the increasing concern about biometric template protection [1]. Some proposed systems, such as fuzzy commitment [2], fuzzy extractor [3, 4], secure sketch [5], and helper data systems [6,7,8,9], employ a binary biometric representation. The quality of the binary string is crucial to their performances. Extracting binary biometric strings is of great significance. A biometric system with binary representation can be generalized into the following three modules

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Conclusion