Printed Chinese Character Recognition Based on Pixel Distribution Probability of Character Image

This paper analyzed the disadvantage of the character recognition method of Casey and Nagy. It adopted advantage of two methods and proposed a new method of character recognition. In this method, the pixel distribution probability of character image is the basal index. The minimal distance product and the maximal fuzzy correlation measure are the evaluation index. It not only overcame the shortcoming of above two methods but also improved the rate of character recognition. With the recognition experiment of 3500 printed Chinese characters, the result showed that this method is accurate and effective since the recognition rate of single character exceeded 99.97%.