• DocumentCode
    3549006
  • Title

    3D geometric and optical modeling of warped document images from scanners

  • Author

    Zhang, Li ; Zhang, Zheng ; Tan, Chew Lim ; Xia, Tao

  • Author_Institution
    Sch. of Comput., National Univ. of Singapore, Singapore
  • Volume
    1
  • fYear
    2005
  • fDate
    20-25 June 2005
  • Firstpage
    337
  • Abstract
    When one scans a document page from a thick bound volume, the curvature of the page to be scanned results in two kinds of distortion in the scanned document images: i) shade along the ´spine´ of the book; and ii) warping in the shade area. In this paper, we propose an efficient restoration method based on the discovery of the 3D shape of a book surface from the shading information in a scanned document image. We first build practical models namely a 3D geometric model and a 3D optical model for the practical scanning conditions to reconstruct the 3D shape of book surface. We next restore the scanned document image using this shape based on de-shading and de-warping models. Finally, we evaluate the restoration results by comparing the OCR (optical character recognition) performance on the original and restored document images. The experiments show that the geometric and photometric distortions are mostly removed and the OCR results are improved markedly.
  • Keywords
    document image processing; image restoration; image scanners; optical character recognition; stereo image processing; 3D geometric modeling; 3D optical modeling; 3D shape reconstruction; book surface; de-shading models; de-warping models; document page; geometric distortions; optical character recognition; page curvature; photometric distortions; restoration method; scanned document images; scanners; shading information; warped document images; Books; Geometrical optics; Image reconstruction; Image restoration; Optical character recognition software; Optical distortion; Optical variables control; Shape; Solid modeling; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-2372-2
  • Type

    conf

  • DOI
    10.1109/CVPR.2005.11
  • Filename
    1467287