An a-contrario biometric fusion approach
Luis Di Martino, Javier Preciozzi, Rafael Grompone von Gioi, Guillermo Garella, Alicia Fernández, Federico Lecumberry
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 14-19 jun, page 822--823- 2020
Research group(s):  Tratamiento de Imagenes (gti)
Department(s):  Procesamiento de Señales
Download the publication : DPGGFL20.pdf [882KB]  

Abstract

Fusion is a key component in many biometric systems: it is one of the most widely used techniques to improve their accuracy. Each time we need to combine the output of systems that use different biometric traits, or different samples of the same biometric trait, or even different algorithms, we need to define a fusion strategy. Independently of the fusion method used, there is always a decision step, in which it is decided if the traits being compared correspond to the same individual or not. In this work, we present a statistical decision criterion based on the a-contrario framework, which has already proven to be useful in biometric applications. The proposed method and its theoretical background is described in detail, and its application to biometric fusion is illustrated with simulated and real data.

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» Luis Di Martino
» Javier Preciozzi
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» Alicia Fernández
» Federico Lecumberry