• DocumentCode
    2888748
  • Title

    Intelligent Stolen Vehicle Detection using Video Sensing

  • Author

    Al-Hmouz, Rami ; Challa, Subhash

  • Author_Institution
    Univ. of Technol. Sydney, Sydney
  • fYear
    2007
  • fDate
    12-14 Feb. 2007
  • Firstpage
    302
  • Lastpage
    307
  • Abstract
    This paper focuses on the problem of color recognition from natural images under various illumination conditions. The most likely colors of the vehicle are estimated in different regions of the car image around the plate and the results from these regions are fused using the famous Bayes´ rule. The application of the information fusion enhanced color recognition technology in stolen vehicle identification is also proposed in this paper. The basic approach is based on jointly estimating the license plate characters and other features of the car like its color and type and matching them with the registered car databases. If there is an inconsistency, the proposed method classifies the vehicle under observation as possibly stolen.
  • Keywords
    Bayes methods; image colour analysis; image recognition; natural scenes; sensor fusion; traffic engineering computing; Bayes rule; enhanced color recognition; illumination condition; information fusion; intelligent stolen vehicle detection; natural images; stolen vehicle identification; video sensing; Character recognition; Histograms; Image recognition; Intelligent control; Intelligent sensors; Intelligent vehicles; Licenses; Lighting; Pattern recognition; Vehicle detection; ALPR; Color Recognition; Pattern Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Decision and Control, 2007. IDC '07
  • Conference_Location
    Adelaide, Qld.
  • Print_ISBN
    1-4244-0902-0
  • Electronic_ISBN
    1-4244-0902-0
  • Type

    conf

  • DOI
    10.1109/IDC.2007.374567
  • Filename
    4252519