An Intelligent Radical-based On-Line Chinese Character Recognition System

Abstract

An intelligent radical-based on-line Chinese character recognition (OLCCR) system is proposed. We make use of the characteristic that most Chinese characters possess radicals and develop a radicalbased preclassification technique. In the procedure of recognizing radicals, potential candidate radicals are identified from an input character first and then matched with radical templates. Based on the matched radicals, corresponding candidate characters with a smaller matching distance are thus identified. Postprocessing, which utilizes the information of the first and last stable line segments, is incorporated to improve the recognition accuracy. Experiments are carried out to evaluate the performance of the proposed OLCCR system and the average recognition rate is improved from 96.06 to 96.52% if only the first winner is selected and the average recognition time is shortened by about 44%.