• DocumentCode
    2840464
  • Title

    A simple OCR method from strong perspective view

  • Author

    Ko, Mi-Ae ; Kim, Young-Mo

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Kyungpook Nat. Univ., Daegu, South Korea
  • fYear
    2004
  • fDate
    13-15 Oct. 2004
  • Firstpage
    235
  • Lastpage
    240
  • Abstract
    Among many practical factors that need to be considered for a reliable character recognition system in 3D space, the location of the visual angle of a camera might play a crucial role. Different viewpoints in 3D space produces distorted license plate images in a camera. For this reason, a method is developed to segment and to recognize characters of license plate objects undergoing variant perspective view. A method for segmenting license plate characters on a moving vehicle in actual outdoor environment is based upon object contours. And the proposed method for recognizing is constructed from a feature-based approach, parameterized by an affine invariant parameters and the affine invariant features. Experimental results show that the performance of the proposed method is simple and robust, particularly when objects are heavily distorted with strong perspective view.
  • Keywords
    image segmentation; optical character recognition; road vehicles; traffic engineering computing; 3D space; affine invariant features; affine invariant parameters; camera visual angle; character recognition system; distorted license plate images; license plate characters segmentation; moving vehicle; object contours; simple OCR method; variant perspective view; Cameras; Character recognition; Image recognition; Image segmentation; Licenses; Optical character recognition software; Optical distortion; Robustness; Shape; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
  • ISSN
    1550-5219
  • Print_ISBN
    0-7695-2250-5
  • Type

    conf

  • DOI
    10.1109/AIPR.2004.8
  • Filename
    1409704