Quality Controlled Multimodal Fusion of Biometric Experts

The quality of biometric samples used by multi-modal biometric experts to produce matching scores has a significant impact on their fusion. The authors address the problem of quality controlled fusion of multiple biometric experts and focus on the fusion problem in a scenario where biometric trait quality expressed in terms of quality measures can be coarsely quantised. They develop a fusion methodology based on fixed rules that exploit the respective advantages of the sum and product rules and can be easily trained. They show in experimental studies on the XM2VTS database that the proposed method is very promising.