CLC number: TP391.4
On-line Access: 2010-11-04
Received: 2010-09-14
Revision Accepted: 2010-09-26
Crosschecked: 2010-09-14
Cited: 1
Clicked: 8436
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.
@article{title="CMSOF: a structured data organization framework for scanned Chinese medicine books in digital libraries",
author="Jie Yuan, Bao-gang Wei, Li-dong Wang, Wei-ming Lu, Yue-ting Zhuang",
journal="Journal of Zhejiang University Science C",
volume="11",
number="11",
pages="882-892",
year="2010",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1001007"
}
%0 Journal Article
%T CMSOF: a structured data organization framework for scanned Chinese medicine books in digital libraries
%A Jie Yuan
%A Bao-gang Wei
%A Li-dong Wang
%A Wei-ming Lu
%A Yue-ting Zhuang
%J Journal of Zhejiang University SCIENCE C
%V 11
%N 11
%P 882-892
%@ 1869-1951
%D 2010
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1001007
TY - JOUR
T1 - CMSOF: a structured data organization framework for scanned Chinese medicine books in digital libraries
A1 - Jie Yuan
A1 - Bao-gang Wei
A1 - Li-dong Wang
A1 - Wei-ming Lu
A1 - Yue-ting Zhuang
J0 - Journal of Zhejiang University Science C
VL - 11
IS - 11
SP - 882
EP - 892
%@ 1869-1951
Y1 - 2010
PB - Zhejiang University Press & Springer
ER -
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.
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