• DocumentCode
    2799448
  • Title

    Integrated speed limit detection and recognition from real-time video

  • Author

    Eichner, Marcin L. ; Breckon, Toby P.

  • Author_Institution
    Cranfield Univ., Cranfield
  • fYear
    2008
  • fDate
    4-6 June 2008
  • Firstpage
    626
  • Lastpage
    631
  • Abstract
    Here we propose a complete system for robust detection and recognition of the current speed sign restrictions from a moving road vehicle. This approach includes the detection and recognition of both numerical limit and national limit (cancellation) signs with the addition of automatic vehicle turn detection. The system utilizes both RANSAC-based colour-shape detection of speed limit signs and neural network based recognition whilst turn analysis relies on an optic flow based method. As primary detection is based on a robust colour and shape detection methodology this results in a real-time algorithm that is invariant to variable road conditions. The integration of both limit, cancellation and vehicle turn detection within the bounds of real-time system performance represents an advance on prior work within this field.
  • Keywords
    image colour analysis; image motion analysis; image recognition; neural nets; object detection; random processes; real-time systems; road vehicles; sampling methods; traffic engineering computing; video signal processing; RANSAC-based colour-shape detection; image colour; moving road vehicle; national limit sign; neural network; numerical limit sign; optic flow; real-time system; real-time video; speed limit detection; speed limit recognition; speed limit sign; speed sign restriction; turn analysis; vehicle turn detection; Image motion analysis; Neural networks; Optical computing; Optical fiber networks; Real time systems; Road vehicles; Robustness; Shape; System performance; Vehicle detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2008 IEEE
  • Conference_Location
    Eindhoven
  • ISSN
    1931-0587
  • Print_ISBN
    978-1-4244-2568-6
  • Electronic_ISBN
    1931-0587
  • Type

    conf

  • DOI
    10.1109/IVS.2008.4621285
  • Filename
    4621285