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  • 标题:Solving the Binarization Challenges in Document Images Using OTSU Multilevel
  • 本地全文:下载
  • 作者:Enas M. Elgbbas ; Mahmoud I. Khalil ; Hazem Abbas
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2019
  • 卷号:9
  • 期号:7
  • 页码:199-216
  • DOI:10.5121/csit.2019.90715
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:This paper introduces a method for binarization of historical document images that suffer from non-uniform background, faint text, low contrast, stain, bleed-through, or shadow challenges. The proposed method adaptively detects the non-uniform background in the document image and eliminates it. Areas that contain missing text are adaptively identified and reprocessed separately. Stain and bleed-through objects are found depending on stroke width and locally binarized. Shadow is detected based on the image contrast. Otsu multilevel is applied for binarization. DIBCO series is used for testing.
  • 关键词:Document image binarization; Otsu multilevel
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