1997 Fiscal Year Final Research Report Summary
NEW CHARACTER RECOGNITION SYSTEM BASED ON STRUCTURAL INFORMATION OF CHARACTERS
| Project/Area Number |
07458071
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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 | 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 | JAPAN ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY,HOKURIKU |
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Principal Investigator |
KIMURA Masayuki JAPAN ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY,HOKURIKU SCHOOL OF INFORMATION SCIENCE,PROFESSOR, 情報科学研究科, 教授 (50006219)
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| Co-Investigator(Kenkyū-buntansha) |
OMACHI Schin'itiro JAPAN ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY,HOKURIKU SCHOOL OF ENGINEERIN, 工学研究科, 助手 (30250856)
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| Project Period (FY) |
1995 – 1997
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| Keywords | CLASSIFICATION OF DICTIONARY / CHARACTER RECOGNITION / FAST CHARACTER RECOGNITION / STRUCTURAL PARAMETERS / STRUCTURAL INFORMATION |
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| Research Abstract |
The purpose of the research project is to solve the problem to classify a large dictionary for printed character recognition into a large number of small dictionaries, which results in solving drastically the problem to make the character recognition faster. We have attained the purpose through the development of a new technique and an algorithm to use some structural parameters of characters suitable for classification of the set of characters to be recognized into twu groups with sufficiently high accuracy.
These structural parameters are mainly concerned with the structural complexity of characters especially peculiar to Japanese characters, e.g., 'Kana' and 'Kanji' and also with the configuration of histograms of characters. On the other hand, the extreamely high accuracy of classification is obtained by introducing the region called as a gray zone to be defined in the neighbor of the boundary of two groups of characters and to allow every character existing in the gray zone to belog to both groups.
It is certainly expected that our technique and algorithm developed in the resarch project will make such character recognition systems as based on pattern matching at least five times as fast as usual ones by classifying a large dictionary for recognition into may small dictionaries.
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