Error Handling in Multimodal Biometric Systems using Reliability Measures

In this paper, we present a framework for predicting and correcting classification decision errors based on modality reliability measures in a multimodal biometric system. In our experiments we use face and speech experts based on a recently proposed framework which uses Bayesian networks. The expert decisions and the accompanying information on their reliability are combined in a decision module that produces the final verification decision. The proposed system is consequently shown to yield higher decision accuracy than the corresponding unimodal systems.

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 Record created 2006-12-07, last modified 2018-01-27

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