JOURNAL ARTICLE

An Adaptive Binarization Algorithm for Degraded Document Images

Jae-Hyon JuJeong-Su Oh

Year: 2012 Journal:   The Journal of Korean Institute of Communications and Information Sciences Vol: 37 (7A)Pages: 581-585   Publisher: THE KOREAN INSTITUTE OF COMMUNICATIONS AND INFORMATION SCIENCES (KICS)

Abstract

본 논문은 인쇄체 한글과 한자를 포함하는 저화질 문서영상에 효과적인 이진화 알고리즘을 제안하다. 가는 가로획과 굵은 세로획으로 구성된 문자 속성 때문에 기존 알고리즘은 저화질 문서영상에서 세로획보다 약한 성분을 갖는 가로획을 쉽게 검출할 수 없다. 제안된 알고리즘은 전방향 참조 적응적 알고리즘에 수직 방향 참조 알고리즘을 추가하여 기존 알고리즘이 갖는 문제를 해결한다. 실험 결과는 제안된 알고리즘이 다양한 저화질 문서영상들에서 문자를 잘 추출하는 것을 보여주고 있다. This paper proposes an adaptive binarization algorithm which is highly effective for a degraded document image including printed Hangul and Chinese characters. Because of the attribute of character composed of thin horizontal strokes and thick vertical strokes, the conventional algorithms can't easily extract horizontal strokes which have weaker components than vertical ones in the degraded document image. The proposed algorithm solves the conventional algorithm's problem by adding a vertical-directional reference adaptive binarization algorithm to an omni-directional reference one. The simulation results show the proposed algorithm extracts well characters from various degraded document images.

Keywords:
Computer science Algorithm Character (mathematics) Image (mathematics) Artificial intelligence Computer vision Pattern recognition (psychology) Horizontal and vertical Mathematics

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Citation History

Topics

Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology

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