Abstract
This paper proposes an efficient probabilistic indexing scheme called P robabilistic R etrieval-Tree(PR-Tree) to facilitate a efficient probabilistic retrieval of Chinese calligraphic manuscript images based on triple features such as contour points, character styles and number of strokes. To the best of our understanding, this is first work on probabilistic retrieval over Chinese character. Different from conventional character retrieval and indexing methods [18] which only adopts shape similarity as a query metric, our proposed indexing algorithm allows user to choose the above three kinds of features as query elements. Moreover, a probabilistic model is introduced into the character retrieval process. Comprehensive experiments are conducted to testify the effectiveness and efficiency of our proposed retrieval and indexing methods respectively.
This paper is partially supported by the Program of National Natural Science Foundation of China under Grant No. 60003047,No.60873022, No.60903053; The Program of Natural Science Foundation of Zhejiang Province under Grant No. Z1100822,No.Y1080148, No.Y1090165; The Science Fund for Young Scholars of Zhejiang Gongshang University under Grant No. G09-7.
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Zhuang, Y. (2010). Web-Based Probabilistic Retrieval of Chinese Calligraphic Character Images: An Efficiency Study. In: Luo, X., Spaniol, M., Wang, L., Li, Q., Nejdl, W., Zhang, W. (eds) Advances in Web-Based Learning – ICWL 2010. ICWL 2010. Lecture Notes in Computer Science, vol 6483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17407-0_36
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DOI: https://doi.org/10.1007/978-3-642-17407-0_36
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