Literature DB >> 15376895

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

Cheng-Lin Liu1, Stefan Jaeger, Masaki 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.

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Year:  2004        PMID: 15376895     DOI: 10.1109/TPAMI.2004.1262182

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  4 in total

1.  Influence of graphical weights' interpretation and filtration algorithms on generalization ability of neural networks applied to digit recognition.

Authors:  Maciej Kusy; Damian Szczepanski
Journal:  Neural Comput Appl       Date:  2011-11-11       Impact factor: 5.606

2.  The proximate unit in Chinese handwritten character production.

Authors:  Jenn-Yeu Chen; Rong-Ju Cherng
Journal:  Front Psychol       Date:  2013-08-09

3.  PF-ViT: Parallel and Fast Vision Transformer for Offline Handwritten Chinese Character Recognition.

Authors:  Yongping Dan; Zongnan Zhu; Weishou Jin; Zhuo Li
Journal:  Comput Intell Neurosci       Date:  2022-09-28

4.  S-Swin Transformer: simplified Swin Transformer model for offline handwritten Chinese character recognition.

Authors:  Yongping Dan; Zongnan Zhu; Weishou Jin; Zhuo Li
Journal:  PeerJ Comput Sci       Date:  2022-09-20
  4 in total

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