Segmentation of handwritten characters for digitalizing Korean historical documents

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The historical documents are valuable cultural heritages and sources for the study of history, social aspect and life at that time. The digitalization of historical documents aims to provide instant access to the archives for the researchers and the public, who had been endowed with limited chance due to maintenance reasons. However, most of these documents are not only written. by hand in ancient Chinese characters, but also have complex page layouts. As a result, it is not easy to utilize conventional OCR(optical character recognition) system about historical documents even if OCR has received the most attention for several years as a key module in digitalization. We have been developing OCR-based digitalization system of historical documents for years. In this paper, we propose dedicated segmentation and rejection methods for OCR of Korean historical documents. Proposed recognition-based segmentation method uses geometric feature and context information with Viterbi algorithm. Rejection method uses Mahalanobis distance and posterior probability for solving out-of-class problem, especially. Some promising experimental results are reported.
Publisher
SPRINGER-VERLAG BERLIN
Issue Date
2004
Language
English
Article Type
Article; Proceedings Paper
Citation

DOCUMENT ANALYSIS SYSTEMS VI, PROCEEDINGS BOOK SERIES: LECTURE NOTES IN COMPUTER SCIENCE, v.3163, pp.114 - 124

ISSN
0302-9743
URI
http://hdl.handle.net/10203/85198
Appears in Collection
CS-Journal Papers(저널논문)
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