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

Multi-biometrics aims at building more accurate unified biometric 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 multibiometric 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.