Research on High Performance Mathematical Expression Recognition Method for Digitization of Scientific Documents
| Project/Area Number |
12680411
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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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 | Shinshu University |
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Principal Investigator |
OKAMOTO Masayuki Shinshu University, Faculty of Engineering, Professor, 工学部, 教授 (50109196)
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| Project Period (FY) |
2000 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥2,900,000 (Direct Cost: ¥2,900,000)
Fiscal Year 2001: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2000: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | Formula Recognition / Document Image Processing / Character Recognition / Pattern Recognition |
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| Research Abstract |
In this research, a new mathematical expression recognition system based on our former system has been developed, and intensive experimentations were curried out for mathematical journals. The subjects of our improvement are as follows;
( 1 ) Collection of a large numbers of characters and symbols used in mathematical expressions.
( 2 ) Improvement of a algorithm which can deal with touching and separated characters or symbols.
( 3 ) Recognition of wide variety of Matrices and conditional expressions.
( 4 ) Improvement of script expression recognition.
( 5 ) Development of a quantitative performance evaluation method for mathematical expression recognition.
( 6 ) Construction of a grand truth database.
For the subject ( 1 ), various characters and symbols were collected from the journals "Archiv der Mathematik vol. 60-65" which is the documents we are working on the joint project with Essen University, Germany. For ( 2 ), some improvements were made, but this is one of our future works. For ( 3 ), matrices including other matrices or abbreviation symbols as elements can be recognized fairlywell. For ( 4 ), the recognition rate for long script expressions was improved due to construction of anewdictionaryof small sized fonts. For ( 5 ), recognition results for each sub-expressions are presented in mathML formats, and compared automaticallywith the grand truth database developed in the subject ( 6 ). This method enables us to develop our mathematical expression recognition system efficiently. As a result, we confirmed that our recognition system can be used for real applications.
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Report
(3 results)
Research Products
(12 results)
