Unification of Evidence-Theoretic Fusion Algorithms: A Case Study in Level-2 and Level-3 Fingerprint Features

Mayank Vatsa, Richa Singh, Afzel Noore
2009 IEEE transactions on systems, man and cybernetics. Part A. Systems and humans  
This paper formulates an evidence theoretic multimodal fusion approach using belief functions that takes into account the variability in image characteristics. When processing non-ideal images the variation in the quality of features at different levels of abstraction may cause individual classifiers to generate conflicting genuine-impostor decisions. Existing fusion approaches are non-adaptive and do not always guarantee optimum performance improvements. We propose a contextual unification
more » ... ework to dynamically select the most appropriate evidence theoretic fusion algorithm for a given scenario. The effectiveness of our approach is experimentally validated by fusing match scores from level-2 and level-3 fingerprint features. Compared to existing fusion algorithms, the proposed approach is computationally efficient, and the verification accuracy is not compromised even when conflicting decisions are encountered.
doi:10.1109/tsmca.2008.2007981 fatcat:xsavaekx4nf6zn7rgitddzighi