Error exponent analysis of person identification based on fusion of dependent/independent modalities

摘要

In this paper we analyze performance limits of multimodal biometric identification systems. We consider impact of the inter-modal dependencies on the attainable probabilities of error and demonstrate that an expected performance gain from fusion of dependent modalities is significantly higher than in the case when one fuses independent signals. Finally, in order to demonstrate the efficiency of dependent modality fusion, we perform the problem analysis in the Gaussian formulation and show the performance enhancement versus the independent case.