Online recognition of Chinese characters: the state-of-the-art

IEEE Transactions on Pattern Analysis and Machine Intelligence
Cheng-Lin LiuMasaki Nakagawa

Abstract

Online handwriting recognition is gaining renewed interest owing to the increase of pen computing applications and new pen input devices. The recognition of Chinese characters is different from western handwriting recognition and poses a special challenge. To provide an overview of the technical status and inspire future research, this paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s. Compared to the research in the 1980s, the research efforts in the 1990s aimed to further relax the constraints of handwriting, namely, the adherence to standard stroke orders and stroke numbers and the restriction of recognition to isolated characters only. The target of recognition has shifted from regular script to fluent script in order to better meet the requirements of practical applications. The research works are reviewed in terms of pattern representation, character classification, learning/adaptation, and contextual processing. We compare important results and discuss possible directions of future research.

References

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Citations

Aug 24, 2013·IEEE Transactions on Pattern Analysis and Machine Intelligence·Xiang-Dong ZhouMasaki Nakagawa
Mar 29, 2008·IEEE Transactions on Pattern Analysis and Machine Intelligence·Jia Zeng, Zhi-Qiang Liu
Jun 14, 2008·IEEE Transactions on Pattern Analysis and Machine Intelligence·Neila MezghaniMohamed Cheriet
Mar 31, 2009·Human Movement Science·M Djioua, R Plamondon
Jun 1, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence·Daniel KeysersVictor Carbune
Apr 25, 2017·IEEE Transactions on Pattern Analysis and Machine Intelligence·Xu-Yao ZhangYoshua Bengio

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