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Hierarchical Approximate Matching for Retrieval of Chinese Historical Calligraphy Character

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Abstract

As historical Chinese calligraphy works are being digitized, the problem of retrieval becomes a new challenge. But, currently no OCR technique can convert calligraphy character images into text, nor can the existing Handwriting Character Recognition approach does not work for it. This paper proposes a novel approach to efficiently retrieving Chinese calligraphy characters on the basis of similarity: calligraphy character image is represented by a collection of discriminative features, and high retrieval speed with reasonable effectiveness is achieved. First, calligraphy characters that have no possibility similar to the query are filtered out step by step by comparing the character complexity, stroke density and stroke protrusion. Then, similar calligraphy characters are retrieved and ranked according to their matching cost produced by approximate shape match. In order to speed up the retrieval, we employed high dimensional data structure — PK-tree. Finally, the efficiency of the algorithm is demonstrated by a preliminary experiment with 3012 calligraphy character images.

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Authors and Affiliations

  1. Institute of Artificial Intelligence, Zhejiang University, Hangzhou, 310027, China

    Xia-Fen Zhang, Yue-Ting Zhuang, Jiang-Qin Wu & Fei Wu

  2. College of Information Engineering, Shanghai Maritime University, Shanghai, 200135, China

    Xia-Fen Zhang

Authors
  1. Xia-Fen Zhang
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  2. Yue-Ting Zhuang
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  3. Jiang-Qin Wu
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  4. Fei Wu
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Corresponding author

Correspondence to Xia-Fen Zhang.

Additional information

Supported by the National Natural Science Foundation of China (Grant Nos. 60533090, 60525108), the National Grand Fundamental Research 973 Program of China (Grant No. 2002CB312101), the Science and Technology Project of Zhejiang Province (2005C13032, 2005C11001-05), and the China-US Million Book Digital Library Project (www.cadal.zju.edu.cn).

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Zhang, XF., Zhuang, YT., Wu, JQ. et al. Hierarchical Approximate Matching for Retrieval of Chinese Historical Calligraphy Character. J Comput Sci Technol 22, 633–640 (2007). https://doi.org/10.1007/s11390-007-9077-8

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  • DOI: https://doi.org/10.1007/s11390-007-9077-8

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