지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 중앙대학교 영상콘텐츠융합연구소 TECHART: Journal of Arts and Imaging Science TECHART: Journal of Arts and Imaging Science Vol.1 No.4
- 발행연도
- 2014.11
- 수록면
- 49 - 53 (5page)
- DOI
- 10.15323/techart.2014.11.1.4.49
이용수
초록· 키워드
오류제보하기
In this paper, we present an efficient and adaptive method for document image binarization using degraded images. Our contributions lead to improvements in both the binarization quality and speed. The vertical and horizontal strokes of Korean and Chinese characters are detected adaptively using a local means for accurate binarization. A down-sampled integral image is employed to quickly compute the local means. The proposed method can deal with various degradations owing to shadows, non-uniform illumination, low contrast, and high levels of signal-dependent noise. The experimental results show that the proposed method is about 11- to 424-times faster than existing algorithms and provides better quality results. Therefore, the proposed efficient document binarization algorithm can be a useful tool in fast documentation and optical character recognition.
목차
Abstract
1. Introduction
2. Proposed Method
3. Experimental Results
4. Conclusion
References
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UCI(KEPA) : I410-ECN-0101-2015-680-002827217