• DocumentCode
    1742754
  • Title

    Application of planar motion segmentation for scene text extraction

  • Author

    Gandhi, Tarak ; Kasturi, Rangachar ; Antani, Sameer

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Pennsylvania State Univ., University Park, PA, USA
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    445
  • Abstract
    This paper explores an approach for extracting scene text from a sequence of images with relative motion between the camera and the scene. It is assumed that the scene text lies on planar surfaces, whereas the other features are likely to be at random depths or undergoing independent motion. The motion model parameters of these planar surfaces are estimated using gradient based methods, and multiple motion segmentation. The equations of the planar surfaces, as well as the camera motion parameters are extracted by combining the motion models of multiple planar surfaces. This approach is expected to improve the reliability and robustness of the estimates, which are used to perform perspective correction on the individual surfaces. Perspective correction can lead to improvement in OCR performance. This work can be useful for detecting road signs and bill-boards from a moving vehicle
  • Keywords
    computer vision; feature extraction; image segmentation; image sequences; motion estimation; optical character recognition; character recognition; feature extraction; gradient methods; image sequences; motion estimation; parameter estimation; planar motion segmentation; scene text extraction; Cameras; Computer vision; Equations; Layout; Motion estimation; Motion segmentation; Optical character recognition software; Roads; Robustness; Vehicle detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2000. Proceedings. 15th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-0750-6
  • Type

    conf

  • DOI
    10.1109/ICPR.2000.905372
  • Filename
    905372