• DocumentCode
    2349205
  • Title

    A model-based road sign identification system

  • Author

    Lauzière, Yves Bérubé ; Gingras, Denis ; Ferrie, Frank P.

  • Author_Institution
    Centre for Intelligent Machines, McGill Univ., Montreal, Que., Canada
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Abstract
    A road sign (RS) recognition system poses a real challenge for machine vision. It must recognize a wide variety of RSs under considerable variations in illumination and imaging geometry-all in real-time. Such a system is presented, with emphasis on the system architecture and specific model-based techniques used in the different processing steps. Central to this are a unique physics-based color detection approach and a novel template matching scheme for planar objects. Since the approach strongly relies on modelling for both detection and recognition, it offers the advantage of being reconfigurable by changing only a few parameters. The system is modular with respect to the sensor and the recognition data structure is simple to extend and maintain, and is easily adaptable to different regulations, e.g. North American vs European RSs. The data needed for recognition is computed automatically by modelling image formation with a few geometrical parameters. Experimental results are presented which demonstrate the performance of the system in a real task environment with high overall performance.
  • Keywords
    automated highways; computer vision; image colour analysis; image matching; modelling; illumination; image formation; imaging geometry; machine vision; model-based road sign identification system; modelling; physics-based color detection approach; planar objects; recognition data structure; road sign recognition; sensor; system architecture; template matching scheme; Geometry; Image databases; Image recognition; Lighting; Machine intelligence; Machine vision; Object detection; Roads; Solid modeling; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-1272-0
  • Type

    conf

  • DOI
    10.1109/CVPR.2001.990662
  • Filename
    990662