Classification of Machine-Printed and Handwritten Texts Based on the Bayesian Judge

Correct classification of machine printed and handwritten texts is a key problem of getting accurate recognition result. Combining with the development of financial document OCR system, this paper presents a machine printed and handwritten text classification method using Bayes Judge. Based on Bayes Judge, a new separability measure, Judge Divergence, is put forward. A method for evaluating the Bayes Judge function is also presented. Using 12,158 actual bills to test the above method,the accuracy rate is 99.4%,which verifies the effectiveness of the method.