Chinese character recognition: history, status and prospects

Abstract

Chinese character recognition (CCR) is an important branch of pattern recognition. It was considered as an extremely difficult problem due to the very large number of categories, complicated structures, similarity between characters, and the variability of fonts or writing styles. Because of its unique technical challenges and great social needs, the last four decades witnessed the intensive research in this field and a rapid increase of successful applications. However, higher recognition performance is continuously needed to improve the existing applications and to exploit new applications. This paper first provides an overview of Chinese character recognition and the properties of Chinese characters. Some important methods and successful results in the history of Chinese character recognition are then summarized. As for classification methods, this article pays special attention to the syntactic-semantic approach for online Chinese character recognition, as well as the metasynthesis approach for discipline crossing. Finally, the remaining problems and the possible solutions are discussed.

CalliGUI: Interactive Labeling of Calligraphic Character Images

“…Current scanners, fax machines and multifunction printers can all produce page images of writing at a spatial sampling rate (dpi) adequate for classification [9]. It is not unusual to have to enter long passages of text from a printed or hand-written page on which current OCR produces too many errors.…”

Discriminative quadratic feature learning for handwritten Chinese character recognition

“…Handwritten Chinese character recognition (HCCR), which is an integral part of handwritten text recognition [2], is not solved yet despite that it has been studied for about fifty years [3]. Previous methods perform well only on constrained writings [3], but for free handwriting recognition, the performance is not satisfactory [4]. For example, the ICDAR 2013 Chinese handwriting recognition competition reported the best result of isolated character recognition accuracy 94.77% [5].…”

A New Approach to Segmentation of On-Line Persian Cursive Words

“…Online cursive word recognition studies gain more success in Latin and Chinese languages due to frequent researches [1,2,3], while complex structural features in Arabic-based script made online Persian cursive recognition an open field of study.…”