Quantitative analysis of preprocessing techniques for the recognition of handprinted characters

Results of recognition experiments are presented where different preprocessing techniques have been coupled to the front end of a recognition system. Normalization of character dimensions turns out to be the most efficient preprocessing technique. Various other geometrical representations have been examined as well as local operations. Results obtained are discussed with respect to computational effort. Classification experiments were carried out on a character sample of 560 per class. They have been confirmed with a sample containing 3000 characters per class.