A new approach for a priori client threshold estimation in biometric signature recognition based on multiple linear regression

Authors:
Arancha Simon-Hurtado;Esperanza Manso-Martínez;Carlos Vivaracho-Pascual;Juan M. Pascual-Gaspar
Affiliations:
Dep. Informática, University of Valladolid, Valladolid, Spain;Dep. Informática, University of Valladolid, Valladolid, Spain;Dep. Informática, University of Valladolid, Valladolid, Spain;Dep. Informática, University of Valladolid, Valladolid, Spain
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Year:
2012

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Abstract

This paper presents a novel approach to estimate (predict) the a priori client decision threshold for biometric recognition systems based on multiple linear regression. Biometric recognition is a complex classification problem where the goal is to classify a pattern (biometric sample) as belonging or not to a certain class (client). As in other pattern recognition problems, a correct estimation of the decision threshold is essential for optimizing the biometric system's performance. Our proposal is tested in biometric signature recognition, estimating thresholds for different system working points. A theoretical and practical performance analysis is presented, including a comparison with the state of the art, showing the advantages, in system performance, of our proposal.