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Easy recognition of artistic Chinese calligraphic characters

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Abstract

Chinese calligraphy is one of the excellent expressions of Chinese traditional art. But people without domain knowledge of calligraphy can hardly read, appreciate, or learn this art form, due to it contains many brush strokes with unique shapes and complicate structural topological relationship. In this paper, we explore the solution of text sequence recognition of calligraphy, which is a challenging task because traditional algorithms of text recognition can rarely obtain the satisfied results for the varied styles of calligraphy. Therefore, based on a trainable neural network, this paper proposes an easy recognition method, which combines feature sequence extraction based on DenseNet (Dense Convolutional Network) model, sequence modeling and transcription into a consolidated architecture. Compared with previous algorithms for text recognition, it has two distinctive properties: One is to acquire the artistic features on shapes and structures of different styles of calligraphic characters and the other is to handel sequences in arbitrary lengths without character segmentation. Our experimental results prove that in contrast with several common recognition methods, our method of Chinese calligraphic character in diverse styles demonstrates greater robustness, and the recognition accuracy rate reaches 84.70%.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (NSFC) (No. 62072449) and the Fundamental Research Funds for the Central Universities (No. ZQN-710).

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Authors and Affiliations

  1. Huaqiao University, Xiamen, Fujian, China

    Lijie Yang, Zhan Wu & Jixiang Du

  2. State Key Lab of CS, Institute of Software, Chinese Academy of Sciences (CAS) and University of CAS, Beijing, China

    Tianchen Xu & Enhua Wu

  3. FST, University of Macau, Macao SAR., China

    Enhua Wu

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  1. Lijie Yang
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  2. Zhan Wu
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Correspondence to Lijie Yang.

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Yang, L., Wu, Z., Xu, T. et al. Easy recognition of artistic Chinese calligraphic characters. Vis Comput 39, 3755–3766 (2023). https://doi.org/10.1007/s00371-023-03026-2

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