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Graph-matching-based character recognition for Chinese seal images

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Abstract

Recognizing characters in Chinese seal images is important when researching ancient cultural artworks because the seals may contain critical historical information. However, owing to large intraclass variance and a limited number of training samples, recognizing such characters in Chinese seals is challenging. Thus, this study proposes a graph-matching-based method to recognize characters in historical Chinese seal images. In the proposed method, a Chinese seal character is first modeled as a graph representing its underlying geometric structure. Then, two affinity matrices that measure the similarity of nodes and edge pairs are calculated with their local features. Finally, a correspondence matrix is calculated using a graph matching algorithm and the most similar reference is selected as the recognition result. Compared with several existing classification methods for seal image recognition, the proposed graph-matching-based method achieves better results, particularly in the case of limited samples.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 6152010-6001, 61801178), Natural Science Foundation of Hunan Province (Grant No. 2018JJ3071), and by Hunan Key Laboratory of Visual Perception and Artificial Intelligence.

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Authors and Affiliations

  1. College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China

    Bin Sun, Shaojun Hua & Shutao Li

  2. Information Department, Fujitsu Research and Develop Center, Beijing, 100027, China

    Jun Sun

Authors
  1. Bin Sun
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  2. Shaojun Hua
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  3. Shutao Li
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  4. Jun Sun
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Correspondence to Shutao Li.

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Sun, B., Hua, S., Li, S. et al. Graph-matching-based character recognition for Chinese seal images. Sci. China Inf. Sci. 62, 192102 (2019). https://doi.org/10.1007/s11432-018-9724-7

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  • DOI: https://doi.org/10.1007/s11432-018-9724-7

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