• DocumentCode
    1579797
  • Title

    Binarising camera images for OCR

  • Author

    Seeger, Mauritius ; Dance, Christopher

  • Author_Institution
    Xerox Res. Centre Eur., Cambridge, UK
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    54
  • Lastpage
    58
  • Abstract
    We describe a binarisation method designed specifically for OCR of low quality camera images: background surface thresholding or BST. This method is robust to lighting variations and produces images with very little noise and consistent stroke width. BST computes a "surface" of background intensities at every point in the image and performs adaptive thresholding based on this result. The surface is estimated by identifying regions of low-resolution text and interpolating neighbouring background intensities into these regions. The final threshold is a combination of this surface and a global offset. According to our evaluation BST produces considerably fewer OCR errors than Niblack\´s local average method while also being more runtime efficient
  • Keywords
    image segmentation; image sensors; interpolation; optical character recognition; Niblack local average method; OCR; adaptive thresholding; background surface thresholding; binarisation method; camera images; lighting variations; low quality images; low resolution text; neighbouring background intensities; Algorithm design and analysis; Binary search trees; Degradation; Digital cameras; Error analysis; Europe; Feedback; Noise robustness; Optical character recognition software; Runtime;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7695-1263-1
  • Type

    conf

  • DOI
    10.1109/ICDAR.2001.953754
  • Filename
    953754