• DocumentCode
    3502035
  • Title

    Classification of images in fog and fog-free scenes for use in vehicles

  • Author

    Pavlic, Mario ; Rigoll, Gerhard ; Ilic, Slobodan

  • Author_Institution
    Traffic Technol. & Traffic Manage., BMW Group, Munich, Germany
  • fYear
    2013
  • fDate
    23-26 June 2013
  • Firstpage
    481
  • Lastpage
    486
  • Abstract
    Today modern vehicles are often equipped with a camera, which captures the scene in front of the vehicle. The recognition of weather conditions with this camera can help to improve many applications as well as establish new ones. In this article we will show how it is possible to distinguish between scenes with clear and foggy weather situations. The proposed method uses only gray-scale images as input signal and is running in real time. Using spectral features and a simple linear classifier, we can achieve high detection rates in both daytime and night-time scenes. Furthermore, we will show that in our application area these features outperform others.
  • Keywords
    fog; image classification; meteorology; natural scenes; road vehicles; spectral analysis; traffic engineering computing; clear weather situations; daytime scenes; detection rates; fog scene capturing; fog-free scene capturing; foggy weather situations; gray-scale images; image classification; input signal; linear classifier; night-time scenes; spectral features; weather condition recognition; Cameras; Feature extraction; Histograms; Meteorology; Roads; Vectors; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium (IV), 2013 IEEE
  • Conference_Location
    Gold Coast, QLD
  • ISSN
    1931-0587
  • Print_ISBN
    978-1-4673-2754-1
  • Type

    conf

  • DOI
    10.1109/IVS.2013.6629514
  • Filename
    6629514