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The recognition performance of a biometric system varies significantly from one enrolled user to another. As a result, there is a need to tailor the system to each user. This study investigates a relatively new fusion strategy that is both user-specific and selective. By user-specific, we understand that each user in a biometric system has a different set of fusion parameters that have been tuned...
The performance of biometric systems can be significantly affected by changes in signal quality. In this paper, two types of changes are considered: change in acquisition environment and in sensing devices. We investigated three solutions: (i) model-level adaptation, (ii) score-level adaptation (normalisation), and (iii) the combination of the two, called “compound” adaptation. In order to cope with...
This paper presents a test bed, called the Biosecure DS2 score-and-quality database, for evaluating, comparing and benchmarking score-level fusion algorithms for multimodal biometric authentication. It is designed to benchmark quality-dependent, client-specific, cost-sensitive fusion algorithms. A quality-dependent fusion algorithm is one which attempts to devise a fusion strategy that is dependent...
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