A knowledge-based segmentation algorithm for enhanced recognition of handwritten courtesy amounts

A knowledge based segmentation critic algorithm to enhance recognition of courtesy amounts on bank checks is proposed in this paper. This algorithm extracts the context from the handwritten material and uses a syntax parser based on a deterministic finite automaton to provide adequate feedback to enhance recognition. The segmentation critic presented is capable of handling a number of commonly used styles for courtesy amount representation. Both handwritten and machine written numeric strings were utilized to test the efficacy of the preprocessor for the check recognition system described in this paper. The substitution error fell by 1.0% in our early tests.