Research Of Constrained Handwritten Optical Character Recognition

The research object of this system are constrained handwritten characters (including 10 Arabic numerals, 26 capital English letters and 26 small English letters , 62 characters aggregately). The CC-OCR system developed by the author can complete the process from the characters scan input to the computer recognition.This dissertation brings forward and realizes the multilevel classifiable method which is based on characters coding. Above all, this method realizes the first-grade classification by extracting enough effective characters from characters and coding them, to the others which coundn' t be recognized by the first-grade classification, the method will adopt the second-grade classification using template matching to recognize these characters. The emphasis of this method stands on the first-grade classification phase. The experiment proves that this method is feasible and effective.In the pre-processing phase, each character is fed into a pre-processor, this makes feature extraction and recognition easy. In the first-grade classification phase, the dissertation puts forward border-table subtract of maximum and minimum feature left-border-table intermission feature improving width feature crossing amount average feature, these features combines with some existing features, realizes the ability of classification in the first-grade classification phase better.This system is composed of scanner and computer. This program is completed using C and VC++6. 0.