Studies on Development of OCR system for Historical Documents and Application to Technologies in Electronic Dictionary

本研究的目的是建立电子词典，“Kuzushiji Kaidoku dictionary”和“Kuzushiji Yourei dictionary”，用于历史研究，古文字学和文学专家使用计算机破译历史手写文件，包括移动和笔记本风格，并开发可在移动环境中使用的计算机词典。此外，本论文的主要目的是将词典直接应用于上述文献音译支持系统（Historical document OCR）中的文字识别研究，在此期间取得了以下研究成果：(1)作为“Kuzushiji Yourei dictionary”（它允许我们基于笔划（Kihitsu-jun）索引检索字母的形状和字母使用的示例）的索引的图像被输入为具有诸如“Kuzushiji Yourei dictionary code”、“Mojikyo code”和“Shift-JIS”内部代码的属性以及具有“Kuzushiji Yourei dictionary code”、“Mojikyo code”和“Shift-JIS”内部代码的属性的图像。 ...更多信息 建立了电子Moji数据库（2）开发了检索功能，用户可以在上述词典中检索相似字（3）将“n-gram”方法应用于历史文献音译支持系统的研究（历史文档OCR），并且证实了当假定文档中的丢失或缺失字符时，“n-gram”是有效的。（4）为了建立大约240个字符的字符模式字典，（5）将历史文献字符库中的HCD系列第二版作为计算机化词典之一。(a)HCD 2，债券标题行，伏宫善兵卫文件，200行，1，378个字符，二进制格式。(b)HCD 2a，债券标题行，伏宫善兵卫文件，200行，1，378个字符，256个步骤。c HCD 2b，债券标题行，伏宫善兵卫文件，200行，24位1，378字符颜色格式。(d)HCD 3，债务债券的标题行，伏宫善兵文献，183个字符类型，4933个字符，二进制格式（6）使用上述词典执行以标题行为重点的文献中的字符识别。（7）研究了从《Kuzushiji Kaidoku辞典数据库》中提取的笔顺的估计方法。除了有关历史文献音译支持系统的论文外，研究报告（包括本研究的中间版本）分别于2001年3月和2000年3月发表。

The purpose of this research is to build the electronic dictionaries, "Kuzushiji Kaidoku dictionary" and "Kuzushiji Yourei dictionary", used in which the specialist of the historical study, paleography, and literature deciphers the historical handwritten documents using the computer including mobil and note book styles, and to develop the computerized dictionary that can be used in a mobil environment.Moreover, it is to apply the dictionaries directly to the character recognition researches in the transliteration supporting system for historical documents (Historical document OCR) mentioned above.The following research results were obtained during this reserch period.(1) The images which is the index of "Kuzushiji Yourei dictionary" (it allows us to retrieve the shape of letters and examples of letter use based on the stroke (Kihitsu-jun) index) were input as the images with attributes such as "Kuzushiji Yourei dictionary code", "Mojikyo code" and "Shift-JIS" internal code, and an elec … More tronic Moji database was built(2) A retrieval function which the user can search the similar characters in the above-mentioned dictionary was developed(3) The "n-gram" method was applied to the researches in the historical document transliteration supporting system (historical document OCR), and it was confirmed that "n-gram" was effective when the lost or missing charahter in the document was presumed(4) To build the character pattern dictionary of about 240,000 characters on the historical document to be used in the recognition process, a development of segmentation program and the character selection work were carried out(5) The second edition of HCD series below in the historical document character database had been made as one of computerized dictionaries. (a) HCD2, title line for debt bond, Fushimiya Zenbei document, 200 lines, 1,378 characters, and binary format. (b) HCD2a, title line for the bond, Fushimiya Zenbei document, 200 lines, 1,378 characters, and 256 steps. c HCD2b, title line for debt bond, Fushimiya Zenbei document, 200 lines, and 24bits 1,378 character colors format. (d) HCD3, title line for debt bond, Fushimiya Zenbei document, 183 character types, 4933 characters, and binary format(6) The character recognition in the document focused on the title line was carried out using the above-mentioned dictionary. The research of the recognition techniques for matching the character pattern without segmentation for each character in title line was developed(7) Study on estimation for stroke order extracted from "Database of Kuzushiji Kaidoku dictionary" made by the dictionary has been carried out. Research reports including intermediate version for this study were published in March, 2001 and 2000 respectively besides papers regarding the historical document transliteration supporting system Less