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This article is part of the series Biometric Signal Processing.

Open Access Research Article

Handwriting: Feature Correlation Analysis for Biometric Hashes

Claus Vielhauer123* and Ralf Steinmetz1

Author Affiliations

1 Multimedia Communications Lab (KOM), Darmstadt University of Technology, Darmstadt 64283, Germany

2 Platanista GmbH, Dessau 06846, Germany

3 Faculty of Computer Science, Otto-von-Guericke University, Magdeburg 39106, Germany

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EURASIP Journal on Advances in Signal Processing 2004, 2004:389304  doi:10.1155/S1110865704309248

The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2004/4/389304

Received:17 November 2002
Revisions received:9 September 2003
Published:21 April 2004

© 2004 Vielhauer and Steinmetz

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.

biometrics; signature verification; feature evaluation; feature correlation; cryptographic key management; handwriting; information entropy

Research Article