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CLC number: TP391.4

On-line Access: 2010-11-04

Received: 2010-09-14

Revision Accepted: 2010-09-26

Crosschecked: 2010-09-14

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.11 P.882-892

http://doi.org/10.1631/jzus.C1001007


CMSOF: a structured data organization framework for scanned Chinese medicine books in digital libraries


Author(s):  Jie Yuan, Bao-gang Wei, Li-dong Wang, Wei-ming Lu, Yue-ting Zhuang

Affiliation(s):  School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   wbg@zju.edu.cn

Key Words:  Digital library, Chinese medicine, Structured data organization, Cross media, Image separation


Jie Yuan, Bao-gang Wei, Li-dong Wang, Wei-ming Lu, Yue-ting Zhuang. CMSOF: a structured data organization framework for scanned Chinese medicine books in digital libraries[J]. Journal of Zhejiang University Science C, 2010, 11(11): 882-892.

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author="Jie Yuan, Bao-gang Wei, Li-dong Wang, Wei-ming Lu, Yue-ting Zhuang",
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%A Wei-ming Lu
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T1 - CMSOF: a structured data organization framework for scanned Chinese medicine books in digital libraries
A1 - Jie Yuan
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A1 - Li-dong Wang
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A1 - Yue-ting Zhuang
J0 - Journal of Zhejiang University Science C
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1001007


Abstract: 
Organizing unstructured information from books into a well-defined structure is a significant challenge in digital libraries. Most digital libraries can provide only search services at the granularity of books and few libraries allow books to be accessed at the granularity of chapters, as manually constructing directory information for books is time-consuming. Extracting structured data from scanned books thus remains an urgent and important work. In this paper, we propose a novel structured data organization framework called CMSOF to organize scanned data automatically, and apply it to a chinese medicine digital library. In the framework, image blocks and text blocks on the scanned page of books are separated based on the gray histogram projection method or a hybrid method of region growth and the Ada-Boosting classifier at first, and then the text structure is obtained from text blocks by text size and font type recognition. Finally, image blocks and structured OCRed text are correlated at the semantic level. By integrating the structured data into a chinese medicine information system (CMIS), we can organize the chinese medicine books well and users can access the books with flexibility, which indicates that CMSOF is an efficient framework to organize books mixed with images and text.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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