Research on Segmentation and Recognition of Printed Chinese Characters

Abstract

Abstract The printed character recognition (PCR) is an efficient and automatic information entry method, which will become the important function interface of the computer in the future. A good character segmentation method can greatly improve the speed and accuracy of character recognition. This paper proposes a Chinese character segmentation algorithm based on OpenCV open source library and parallel processing, which can segment Chinese characters efficiently and accurately. And then, using the Tesseract-OCR character recognition engine to identify Chinese characters, the experimental results show that the average recognition time of a single Chinese character is 0.07s, and the recognition rate of Chinese characters is 96.2%, which proves the feasibility of the method.