• DocumentCode
    2321819
  • Title

    Speed detection of moving vehicles from one scene of QuickBird images

  • Author

    Liu, Wen ; Yamazaki, Fumio

  • Author_Institution
    Grad. Sch. of Eng., Chiba Univ., Chiba, Japan
  • fYear
    2009
  • fDate
    20-22 May 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A new method is developed to extract moving vehicles and subsequently detect their speeds from a pair of QuickBird (QB) panchromatic (PAN) and multi-spectral (MS) images automatically. Since PAN and MS sensors of QB have a slight time lag, about 0.2 seconds, the speed of moving vehicles can be detected by the movement between PAN and MS images in the time lag. From a PAN image with 0.6 m resolution, vehicles can be extracted by an object-based approach. But it is difficult to extract the accurate position of vehicles from a MS image with 2.4 m resolution. Thus an area correlation method is proposed to estimate the location of vehicles from MS images in a sub-pixel level. Using the results of the vehicle extraction, the speed of moving vehicles can be detected. The approach is tested on several parts of the QB image covering the central Tokyo, Japan, and the accuracy of the result is demonstrated.
  • Keywords
    feature extraction; position measurement; remote sensing; road vehicles; velocity measurement; Japan; QuickBird MS sensors; QuickBird PAN sensors; QuickBird images; QuickBird multispectral images; QuickBird panchromatic images; Tokyo; area correlation method; moving vehicle speed detection; object based approach; vehicle feature extraction; vehicle location estimation; Cities and towns; Data mining; Event detection; Image resolution; Layout; Remote sensing; Satellites; Testing; Vehicle detection; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Urban Remote Sensing Event, 2009 Joint
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3460-2
  • Electronic_ISBN
    978-1-4244-3461-9
  • Type

    conf

  • DOI
    10.1109/URS.2009.5137663
  • Filename
    5137663