| Project/Area Number |
10558056
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
情報システム学(含情報図書館学)
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| Research Institution | KYUSHU UNIVERSITY |
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Principal Investigator |
SUZUKI Masakazu Faculty of Mathematics, Kyushu University, Prof., 大学院・数理研究院, 教授 (20112302)
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| Co-Investigator(Kenkyū-buntansha) |
FUKUDA Ryoji Oita University, Faculty of Engineering, Ass. Prof., 工学部, 助教授 (70238492)
EJIMA Toshiaki Kyushu Inst. of Technology, Faculty of Computer Science and Systems Engineering, Prof., 情報工学部, 教授 (00124553)
TAMARI Fumikazu Fukuoka Univ. of Education, Faculty of Education, Prof., 教育学部, 教授 (70036937)
YAMAGATA Hedeaki Ricoh Co., Ltd., Software Research Center, ソフトウェア所・第2研究室, 研究員
TACHIKAWA Michiyoshi Ricoh Co., Ltd., Software Research Center, ソフトウェア所・第2研究室, 研究室長
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| Project Period (FY) |
1998 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥12,500,000 (Direct Cost: ¥12,500,000)
Fiscal Year 2001: ¥2,000,000 (Direct Cost: ¥2,000,000)
Fiscal Year 2000: ¥2,000,000 (Direct Cost: ¥2,000,000)
Fiscal Year 1999: ¥2,500,000 (Direct Cost: ¥2,500,000)
Fiscal Year 1998: ¥6,000,000 (Direct Cost: ¥6,000,000)
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| Keywords | OCR / Mathematical symbol recognition / Mathematical formual recognition / Document Analysis / Digital library / レイアウト解析 / 文書電子化 / 数学記号認識 / OCR / ヤグメンテーション / 手書き数式認識 / 光学文字認識 |
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| Research Abstract |
In this research, we developed an OCR system adapted to scientific documents, in view of its application to retro-digitization of mathematical journals and automatic Braille transcription of mathematical documents. The target images are those obtained from clearly printed documents by 400-600DPI scanner.
Since there is no commercial OCR software which can recognize mathematical symbols, we developed our own OCR engine. It recognizes with about 450 kinds of characters and symbols used in mathematical expressions, and distinguishes well the italic fonts and upright fonts of alphabets.
For the recognition of text areas, there are several efficient post-processing methods to improve recognition results using linguistic information, while in mathematical expression areas, some other different methods of post-processing based on the structure of mathematical notations are efficient. Therefore, we developed algorithms to separate text area and mathematical expression areas, for both Japanese and English documents.
As for the structure analysis of mathematical expressions, we developed a new method, robust against the recognition errors of characters and similar characters of different sizes. We first construct a network joining characters (symbols) by possible links of relations with cost, Finally, we obtain the result of the recognition of mathematical formulas as the spanning tree of minimum cost of the network, after reevaluating the candidates by using the cost reflecting global structure of the mathematical expressions. The advantage of this method is that local errors of the recognition are recovered automatically by the total cost of the recognition tree.
We also developed handwriting interface to edit mathematical expressions to use it as an easy user interface to correct the recognition errors of mathematical expressions.
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