• DocumentCode
    154572
  • Title

    Detecting symbols on road surface for mapping and localization using OCR

  • Author

    Schreiber, Markus ; Poggenhans, Fabian ; Stiller, Christoph

  • Author_Institution
    Mobile Perception Syst., FZI Res. Center for Inf. Technol., Karlsruhe, Germany
  • fYear
    2014
  • fDate
    8-11 Oct. 2014
  • Firstpage
    597
  • Lastpage
    602
  • Abstract
    In this paper, we present a system to detect symbols on roads (e.g. arrows, speed limits, bus lanes and other pictograms) with a common monoscopic or stereoscopic camera system. No manual labeling of images is necessary since the exact definitions of the symbols in the legal instructions for road paintings are used. With those vector graphics an Optical Character Recognition (OCR) System is trained. If only a monoscopic camera is used, the vanishing point is estimated and an inverse perspective transformation is applied to obtain a distortion free top-view. In case of the stereoscopic camera setup, the 3D reconstruction is projected to a ground plane. TESSERACT, a common OCR system is used to classify the symbols. If odometry or position information is available, a spatial filtering and mapping is possible. The obtained information can be used on one side to improve localization, on the other side to provide further information for planning or generation of planning maps.
  • Keywords
    driver information systems; feature extraction; image classification; image reconstruction; object detection; optical character recognition; roads; 3D reconstruction; OCR system; TESSERACT; driver assistance systems; inverse perspective transformation; optical character recognition; road surface; road symbol detection; symbol classification; vanishing point estimation; Character recognition; Manuals; Optical character recognition software; Optical imaging; Roads;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on
  • Conference_Location
    Qingdao
  • Type

    conf

  • DOI
    10.1109/ITSC.2014.6957755
  • Filename
    6957755