Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Quality-based Score Level Fusion in Multibiometric Systems
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
On combination of face authentication experts by a mixture of quality dependent fusion classifiers
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Q-stack: uni- and multimodal classifier stacking with quality measures
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Improving classification with class-independent quality measures: Q-stack in face verification
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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In this paper we provide a theoretical discussion of the impact of uncertainty in quality measurement on the expected benefits of including biometric signal quality measures in classification. While an ideal signal quality measure should be a precise quantification of the actual signal properties relevant to the classification process, a real quality measurement may be uncertain. We show how does the degree of uncertainty in quality measurement impact the gains in class separation achieved thanks to using quality measures as conditionally relevant classification feature. We demonstrate that while noisy quality measures become irrelevant classification features, they do not impair class separation beyond the baseline result. We present supporting experimental results using synthetic data.