A multimodal biometric system integrates information from multiple biometric sources to
compensate for the limitations in performance of each individual biometric system. We
propose an optimal framework for combining the matching scores from multiple modalities
using the likelihood ratio statistic computed using the generalized densities estimated from
the genuine and impostor matching scores. The motivation for using generalized densities is
that some parts of the score distributions can be discrete in nature; thus, estimating the�…

Multimodal biometric systems consolidate the evidence presented by multiple biometric
sources and typically provide better recognition performance compared to systems based on
a single biometric modality. Although information fusion in a multimodal system can be
performed at various levels, integration at the matching score level is the most common
approach due to the ease in accessing and combining the scores generated by different
matchers. Since the matching scores output by the various modalities are heterogeneous�…