Abstract
This paper proposes an efficient probabilistic indexing scheme called Probabilistic Multiple-Feature-Tree(PMF-Tree) to facilitate an interactive retrieval of Chinese calligraphic manuscript images based on multiple features such as contour points, character styles and types of 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 they prefer to as query elements. Moreover, a probabilistic modal is introduced to refine the retrieval result. 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. The Science & Technology Planning Project of Wenzhou under Grant No. 2010G0066.
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Zhuang, Y., Jiang, N., Hu, H., Hu, H., Jiang, G., Yuan, C. (2011). Probabilistic and Interactive Retrieval of Chinese Calligraphic Character Images Based on Multiple Features. In: Yu, J.X., Kim, M.H., Unland, R. (eds) Database Systems for Advanced Applications. DASFAA 2011. Lecture Notes in Computer Science, vol 6587. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20149-3_23
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DOI: https://doi.org/10.1007/978-3-642-20149-3_23
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