Score Fusion by Maximizing the Area under the ROC Curve

Authors:
Mauricio Villegas;Roberto Paredes
Affiliations:
Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, Valencia, Spain 46022;Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, Valencia, Spain 46022
Venue:
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Year:
2009

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Abstract

Information fusion is currently a very active research topic aimed at improving the performance of biometric systems. This paper proposes a novel method for optimizing the parameters of a score fusion model based on maximizing an index related to the Area Under the ROC Curve. This approach has the convenience that the fusion parameters are learned without having to specify the client and impostor priors or the costs for the different errors. Empirical results on several datasets show the effectiveness of the proposed approach.