• DocumentCode
    3075921
  • Title

    Vision knowledge vectorization: converting raster images into vector form

  • Author

    Jennings, C. ; Parker, J.R.

  • Author_Institution
    Dept. of Comput. Sci., Calgary Univ., Alta., Canada
  • Volume
    1
  • fYear
    1994
  • fDate
    9-13 Oct 1994
  • Firstpage
    311
  • Abstract
    The traditional erosion based vectorization methods create flawed vector representations, which must then be corrected by hand. Some of these flaws are due to artifacts injected by the thinning process, while others are intrinsic to the process-perfect vectorization is not, in general, possible. The approach described here is based on looking at the complete search space, reduced by using knowledge about the image domain-that of engineering diagrams. The search space is reduced far enough that very good line and curve extractions can be performed. The results are compared against traditional vectorization in terms of the time needed by a human to repair the resulting line drawings
  • Keywords
    document image processing; artifacts; curve extractions; engineering diagrams; line extractions; raster images; search space; thinning process; vision knowledge vectorization; Computer science; Computer vision; Data mining; Engineering drawings; Geographic Information Systems; Humans; Image converters; Knowledge engineering; Laboratories; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-8186-6265-4
  • Type

    conf

  • DOI
    10.1109/ICPR.1994.576286
  • Filename
    576286