Segmentation of Handwritten Characters for Digitalizing Korean Historical Documents

  • Min Soo Kim
  • Kyu Tae Cho
  • Hee Kue Kwag
  • Jin Hyung Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3163)


The historical documents are valuable cultural heritages and sources for the study of history, social aspect and life at that time. The digitalization of historical documents aims to provide instant access to the archives for the researchers and the public, who had been endowed with limited chance due to maintenance reasons.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 As a result, it is not easy to utilize conventional OCR(optical character recognition) system about historical documents even if OCR has received the most attention for several years as a key module in digitalization. We have been developing OCR-based digitalization system of historical documents for years. In this paper, we propose dedicated segmentation and rejection methods for OCR of Korean historical documents.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.


Linear Discriminant Analysis Mahalanobis Distance Chinese Character Historical Document Optical Character Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Min Soo Kim
    • 1
  • Kyu Tae Cho
    • 1
  • Hee Kue Kwag
    • 2
  • Jin Hyung Kim
    • 1
  1. 1.CS DivKorea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea
  2. 2.Dongbang SnC Co., Ltd.SeoulKorea

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