Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
563319 | Signal Processing | 2008 | 10 Pages |
Abstract
This paper focuses on the estimation of credence in the correctness of classification decisions produced by a biometric identity verification system. We adopt the concept of decision credence defined in terms of subjective Bayesian degree of belief. We demonstrate how credence estimates can be used to predict verification errors and to rectify them, thus improving the classification performance. We also show how the framework of credence estimation helps handle erroneous classification decisions thanks to seamless incorporation of quality measures. Further, we demonstrate that credence information can be effectively applied to perform fusion of decisions in a multimodal scenario.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Krzysztof Kryszczuk, Andrzej Drygajlo,