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Multi-biometric Score-Level Fusion and the Integration of the Neighbors Distance Ratio

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Image Analysis and Recognition (ICIAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8815))

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Abstract

Multi-biometrics aims at building more accurate unified bio-metric decisions based on the information provided by multiple biometric sources. Information fusion is used to optimize the process of creating this unified decision. In previous works dealing with score-level multi-biometric fusion, the scores of different biometric sources belonging to the comparison of interest are used to create the fused score. The novelty of this work focuses on integrating the relation of the fused scores to other comparisons within a 1:N comparison. This is performed by considering the neighbors distance ratio in the ranked comparisons set within a classification-based fusion approach. The evaluation was performed on the Biometric Scores Set BSSR1 database and the enhanced performance induced by the integration of neighbors distance ratio was clearly presented.

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Correspondence to Alexander Opel .

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Damer, N., Opel, A. (2014). Multi-biometric Score-Level Fusion and the Integration of the Neighbors Distance Ratio. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8815. Springer, Cham. https://doi.org/10.1007/978-3-319-11755-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-11755-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11754-6

  • Online ISBN: 978-3-319-11755-3

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