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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 저널정보
- 한국정보통신학회 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING 2022 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING Vo.13 No.1
- 발행연도
- 2022.1
- 수록면
- 42 - 47 (6page)
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초록· 키워드
오류제보하기
Manchu is a script that is written vertically, from top to bottom, with each letter in a word connected by a central stem. Since there are no spaces between the letters in a given word, a preprocessing method is required in order to extract the individual character units from a given word before any kind of character recognition can be performed.
In this paper, we describe a preprocessing method that effectively divides Manchu script words into individual character units. Unlike existing research that first removes the central stem of a word in order to recognize the remaining pieces to the left and right of the stem, or attempts to perform recognition tasks on whole words and not the individual characters within the words, this method cuts each vertical word horizontally into recognizable character units. Character recognition can then be applied to the individual units that are separated out from each word. The effectiveness of this method was verified on multiple images of Manchu script.
In this paper, we describe a preprocessing method that effectively divides Manchu script words into individual character units. Unlike existing research that first removes the central stem of a word in order to recognize the remaining pieces to the left and right of the stem, or attempts to perform recognition tasks on whole words and not the individual characters within the words, this method cuts each vertical word horizontally into recognizable character units. Character recognition can then be applied to the individual units that are separated out from each word. The effectiveness of this method was verified on multiple images of Manchu script.
목차
Abstract
I. INTRODUCTION
II. EXISTING MANCHU CHARACTER EXTRACTION METHOD
III. SUGGESTED MANCHU CHARACTER EXTRACTION METHOD
IV. EXPERIMENT RESULT
V. CONCLUSION
REFERENCES
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