A Lexicon Driven Approach to Handwritten Word Recognition for Real-Time Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Guide to Biometrics
Using independence assumption to improve multimodal biometric fusion
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Cluster Ensembles Based on Vector Space Embeddings of Graphs
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
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Matching systems can be used in different operation tasks such as verification task and identification task. Different optimization criteria exist for these tasks - reducing cost of acceptance decisions for verification systems and minimizing misclassification rate for identification systems. In this paper we show that the optimal combination rules satisfying these criteria are also different. The difference is caused by the dependence of matching scores produced by a single matcher and assigned to different classes. We illustrate the theory by experiments with biometric matchers and handwritten word recognizers.