Fusion of classifiers with fuzzy integrals

In this paper, an evidence fusion technique, based on the notion of fuzzy integral is utilized to combine (fuse) the results of multiple character classifiers and realize a robust algorithm for high accuracy handwritten character recognition. Both source (classifier) relevance as well as source evidence are utilized to achieve significant enhancements. An algorithm for dynamically assigning source relevance, using the performance matrices of individual classifiers has also been developed. Experiments on a large data set show that a very low error rate and a low rejection rate can be achieved by fusing several simple classifiers