[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.3837/tiis.2011.02.008

Discriminative and Non-User Specific Binary Biometric Representation via Linearly-Separable SubCode Encoding-based Discretization

Lim, Meng-Hui (School of Electrical and Electronic Engineering, College of Engineering, Yonsei University)
Teoh, Andrew Beng Jin (School of Electrical and Electronic Engineering, College of Engineering, Yonsei University)

Publication Information

KSII Transactions on Internet and Information Systems (TIIS) / v.5, no.2, 2011 , pp. 374-388 More about this Journal

Abstract

Biometric discretization is a process of transforming continuous biometric features of an identity into a binary bit string. This paper mainly focuses on improving the global discretization method - a discretization method that does not base on information specific to each user in bitstring extraction, which appears to be important in applications that prioritize strong security provision and strong privacy protection. In particular, we demonstrate how the actual performance of a global discretization could further be improved by embedding a global discriminative feature selection method and a Linearly Separable Subcode-based encoding technique. In addition, we examine a number of discriminative feature selection measures that can reliably be used for such discretization. Lastly, encouraging empirical results vindicate the feasibility of our approach.

Keywords

Biometric; discretization; quantization; encoding; linearly separable subcode;

Citations & Related Records

Times Cited By Web Of Science : 1 (Related Records In Web of Science)
Times Cited By SCOPUS : 1

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