A filtering algorithm for highly noisy images of brazilian ATM bank checks
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
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A segmentation based courtesy amount recognition (CAR) system is presented in this paper. A two-stage segmentation module has been proposed, namely the global segmentation stage and the local segmentation stage. At the global segmentation stage, a courtesy amount is coarsely segmented into sub-images according to the spatial relationships of the connected components. These sub-images are then verified by the recognition module and the rejected sub-images are sequentially split using contour analysis at the local segmentation stage. Two neural network classifiers are combined into a recognition module. The isolated digit classifierdivides the input patterns into ten numeral classes ('0'-'9'), while the holistic double zeros classifier recognizes the cursive and touching double zeros. Experimental results show that the system reads 66.5% bank checks correctly at 0% misreading rate.