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Recognition of courtesy amounts on bank checks based on a segmentation approach

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 classifier divides 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.