Open Access

Handwriting: Feature Correlation Analysis for Biometric Hashes

EURASIP Journal on Advances in Signal Processing20042004:389304

https://doi.org/10.1155/S1110865704309248

Received: 17 November 2002

Published: 21 April 2004

Abstract

In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation), the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches.

Keywords and phrases

biometricssignature verificationfeature evaluationfeature correlationcryptographic key managementhandwritinginformation entropy

Authors’ Affiliations

(1)
Multimedia Communications Lab (KOM), Darmstadt University of Technology
(2)
Platanista GmbH
(3)
Faculty of Computer Science, Otto-von-Guericke University

Copyright

© Vielhauer and Steinmetz 2004