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Front. Inform. Technol. Electron. Eng.  2011, Vol. 12 Issue (11): 873-884    DOI: 10.1631/jzus.C1100005
    
Efficient shape matching for Chinese calligraphic character retrieval
Wei-ming Lu, Jiang-qin Wu*, Bao-gang Wei, Yue-ting Zhuang
School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
Efficient shape matching for Chinese calligraphic character retrieval
Wei-ming Lu, Jiang-qin Wu*, Bao-gang Wei, Yue-ting Zhuang
School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
 全文: PDF(2486 KB)  
摘要： An efficient search method is desired for calligraphic characters due to the explosive growth of calligraphy works in digital libraries. However, traditional optical character recognition (OCR) and handwritten character recognition (HCR) technologies are not suitable for calligraphic character retrieval. In this paper, a novel shape descriptor called SC-HoG is proposed by integrating global and local features for more discriminability, where a gradient descent algorithm is used to learn the optimal combining parameter. Then two efficient methods, keypoint-based method and locality sensitive hashing (LSH) based method, are proposed to accelerate the retrieval by reducing the feature set and converting the feature set to a feature vector. Finally, a re-ranking method is described for practicability. The approach filters query-dissimilar characters using the LSH-based method to obtain candidates first, and then re-ranks the candidates using the keypoint- or sample-based method. Experimental results demonstrate that our approaches are effective and efficient for calligraphic character retrieval.
关键词： Calligraphy;  Shape feature;  Character retrieval;  Efficient matching    
Abstract: An efficient search method is desired for calligraphic characters due to the explosive growth of calligraphy works in digital libraries. However, traditional optical character recognition (OCR) and handwritten character recognition (HCR) technologies are not suitable for calligraphic character retrieval. In this paper, a novel shape descriptor called SC-HoG is proposed by integrating global and local features for more discriminability, where a gradient descent algorithm is used to learn the optimal combining parameter. Then two efficient methods, keypoint-based method and locality sensitive hashing (LSH) based method, are proposed to accelerate the retrieval by reducing the feature set and converting the feature set to a feature vector. Finally, a re-ranking method is described for practicability. The approach filters query-dissimilar characters using the LSH-based method to obtain candidates first, and then re-ranks the candidates using the keypoint- or sample-based method. Experimental results demonstrate that our approaches are effective and efficient for calligraphic character retrieval.
Key words: Calligraphy    Shape feature    Character retrieval    Efficient matching
收稿日期: 2011-01-02 出版日期: 2011-11-04
CLC:  TP391.4  
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Wei-ming Lu
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引用本文:

Wei-ming Lu, Jiang-qin Wu, Bao-gang Wei, Yue-ting Zhuang. Efficient shape matching for Chinese calligraphic character retrieval. Front. Inform. Technol. Electron. Eng., 2011, 12(11): 873-884.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1100005    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2011/V12/I11/873

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