1994 Fiscal Year Final Research Report Summary
An Intelligent Automatic Tranlation System of Printed Document into Braille at high accuracy
| Project/Area Number |
04508001
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| Research Category |
Grant-in-Aid for Developmental Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Research Field |
Informatics
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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, Professor, 情報科学研究科, 教授 (50006219)
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| Co-Investigator(Kenkyū-buntansha) |
SHIMODAIRA Hiroshi Japan Advanced Institute of Science and Technology, Hokuriku, School of Informat, 情報科学研究科, 助教授 (30206239)
ISHIKAWA Jun University of Shizuoka, Dept.of International Relations, 国際関係学部, 助教授 (60192481)
YONEDA Masaaki Toyama University, Faculty of Engineering, Professor, 工学部, 教授 (30019210)
ASO Hirotomo Tohoku University, Faculty of Engineering, Professor, 工学部, 教授 (10005522)
KIZUKA Yasuhiro The National Institute of Special Education, head, 視覚障害教育部, 部長 (90000265)
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| Project Period (FY) |
1992 – 1994
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| Keywords | Automatic transcription into braille / Printed character recognition / Document understanding / Visually-disabled person / Document reader / User-interface / Reading aids |
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| Research Abstract |
The developed system mainly consists of two modules. The first one is the OCR (Optical Character Recognition unit) module which performs the analysis and recognition of scanned text, and the second module outputs the result in the Braille text form.
The main processing unit of the OCR module includes a UNIX workstation and a character recognition device which has been specially developed for this project.
In order to fulfilll the various demands of a visually impaired person, several kinds of texts like magazine (weekly magazine), conference journal, text books, technical books, paperbacks, and other practical documents has been taken into account. For analyzing the structure of a text, page numbers, position of diagrams/tables, captions and ruby characters has been considered for recognition. During experiments the recognition rate for line and diagram detection was 97.4respectively. However, because of the variation of text formats, the recognition rate for detecting caption, page number and foot notes was widely varied.
The developed character recognition unit is able to process 25 to 28 characters per second and it has been confirmed that the present processing speed is 5 to 8 times faster if compared to the method where the processing is done by employing software. By utilizing dictionary and by modifying the algorithm the correct output for Braille text is improved to 99.5The interface design was based on on a cognitive model and its effectiveness is verified by a number of impaired users.
Finally it is necessary to perform research for improving the response in respect to key operations and evaluate the system with the help of a number of visually impaired user.
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