• DocumentCode
    2778329
  • Title

    Colour-based bottom-up saliency for traffic sign detection

  • Author

    Le Ngo, Anh Cat ; Ang, Li-Minn ; Seng, Kah Phooi ; Qiu, Guoping

  • Author_Institution
    Electron. Dept., Univ. of Nottingham, Semenyih, Malaysia
  • fYear
    2010
  • fDate
    5-8 Dec. 2010
  • Firstpage
    427
  • Lastpage
    431
  • Abstract
    On roads, drivers can detect traffic sign extraordinarily fast and accurately; however, the computer vision system does not easily imitate this natural ability although using a lot of image processing techniques. This weakness can be tackled by a bottom-up visual saliency method based on traffic-sign colours which occupy certain ranges of RGB values. These values can be used to modulate the bottom-up visual saliency, so the proposed system can focus on traffic signs detection. The method is tested on the UNMC Automotive Vision Database and compared with results of the purely bottom-up visual saliency method.
  • Keywords
    computer vision; image colour analysis; object detection; traffic engineering computing; UNMC automotive vision database; colour-based bottom-up saliency method; computer vision system; image processing techniques; red-green-blue values; traffic sign detection; Feature extraction; Gaussian distribution; Humans; Image color analysis; Pixel; Roads; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-9054-7
  • Type

    conf

  • DOI
    10.1109/ICCAIE.2010.5735117
  • Filename
    5735117