Damer, NaserNaserDamerNouak, AlexanderAlexanderNouak2022-03-122022-03-122015https://publica.fraunhofer.de/handle/publica/38972810.1109/BIOSIG.2015.7314624This work presents an approach to integrate biometric source weighting in the calculation of neighbors distance ratios to be used within a classification-based multi-biometric fusion process. The neighbors distance ratio represents the elevation of the top ranked identification match to the following ranks. Using biometric source weighing can help achieve more accurate initial identity ranking necessary for neighbors distance ratios. It also influences the effect of each biometric source on the ratios values. The proposed approach is developed and evaluated using the Biometric Scores Set BSSR1 database. The results are presented in the verification scenario as receiver operating curves (ROC). The achieved performance is compared to a number of baseline solutions and a satisfying and stable performance was achieved with a clear benefit of integrating the biometric source weights.enbiometricsbiometric fusiondatabasemeasurementsneural networksCRISPconference paper