Efficient shape matching for Chinese calligraphic character retrieval

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 retri...

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Bibliographic Details
Published in:Frontiers of information technology & electronic engineering 2011-11, Vol.12 (11), p.873-884
Main Authors: Lu, Wei-ming, Wu, Jiang-qin, Wei, Bao-gang, Zhuang, Yue-ting
Format: Article
Language:English
Subjects:
Algorithms
Character recognition
Communications Engineering
Computer Hardware
Computer Science
Computer Systems Organization and Communication Networks
Digital systems
Electrical Engineering
Electronics and Microelectronics
Explosions
Handwriting recognition
Instrumentation
Mathematical analysis
Networks
Optical character recognition
Optimization
Parameter sensitivity
Retrieval
Vectors (mathematics)
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Summary: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.
ISSN:1869-1951
2095-9184
1869-196X
2095-9230
DOI:10.1631/jzus.C1100005