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      영숫자 그림이 혼용된 한글문서에서 문자 분리에 관한 연구 = Segmentation of Characters in Hangul Documents Mixed with Alpanumeric characters and Picture

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      https://www.riss.kr/link?id=A45009304

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      In this paper, we propose a new method for segmenting characters in hangul document mixed with alphanumeric characters and picture. Since hangul has structural characteristics different from those of alphanumeric characters, structural characteristics of hangul characters are also different from those of alphanumeric ones. If hangul and alphanumeric characters are both written in a document, it is difficult to know whether the touching characters are hangul or not.
      The proposed segmentation method uses an MLP to generate candidate cutting points.
      The MLP-based segment lea군 cutting points from training samples which are composed of features extracted from touching character images and correct cutting point of those images. It generates five candidate cutting points per a touching character image and each candidate has a value that is regarded as cutting possibility at that position.
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      In this paper, we propose a new method for segmenting characters in hangul document mixed with alphanumeric characters and picture. Since hangul has structural characteristics different from those of alphanumeric characters, structural characteristics...

      In this paper, we propose a new method for segmenting characters in hangul document mixed with alphanumeric characters and picture. Since hangul has structural characteristics different from those of alphanumeric characters, structural characteristics of hangul characters are also different from those of alphanumeric ones. If hangul and alphanumeric characters are both written in a document, it is difficult to know whether the touching characters are hangul or not.
      The proposed segmentation method uses an MLP to generate candidate cutting points.
      The MLP-based segment lea군 cutting points from training samples which are composed of features extracted from touching character images and correct cutting point of those images. It generates five candidate cutting points per a touching character image and each candidate has a value that is regarded as cutting possibility at that position.

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      목차 (Table of Contents)

      • Ⅰ. 서론
      • Ⅱ. 문서영상 구조 분석
      • 2.1 전처리 과정
      • 2.2 필터링
      • 2.3 기울기 측정
      • Ⅰ. 서론
      • Ⅱ. 문서영상 구조 분석
      • 2.1 전처리 과정
      • 2.2 필터링
      • 2.3 기울기 측정
      • 2.4 연결화소 분리
      • 2.5 영역 결정
      • 2.6 문자 분리
      • Ⅲ. 실험 및 분석
      • 참고문헌
      • 영문초록
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