• DocumentCode
    3070517
  • Title

    Vehicle detection from parking lot aerial images

  • Author

    Huan Wei ; Guoqing Zhou ; Zezhong Zheng ; Xiaowen Li ; Yalan Liu ; Ying Zhang ; Shang Li ; Tao Yue

  • Author_Institution
    Guangxi Key Lab. for Spatial Inf. & Geomatics, Guilin, China
  • fYear
    2013
  • fDate
    21-26 July 2013
  • Firstpage
    4002
  • Lastpage
    4005
  • Abstract
    Vehicle detection from high resolution aerial images has been studied for many years. However, a robust and efficient vehicle detection is still challenging. In this paper, a novel and robust method for automatic vehicle detection from aerial images was presented. In this method, a GIS road vector map is used to constrain a vehicle detection system to parking lot networks, edge detection and morphological preprocessing method are used to identify candidate vehicle pixels. Different types of vehicle templates are selected to adaptively detect the similar vehicles by their correlation coefficient with the same size of the window. Experiment was conducted using 0.15 meter resolution aerial images, the result demonstrated that the new method had an excellent detection performance.
  • Keywords
    edge detection; geographic information systems; geophysical image processing; image resolution; image sensors; road vehicles; GIS road vector map; automatic vehicle detection system; edge detection; morphological preprocessing method; parking lot aerial image resolution; vehicle pixel identification; vehicle template; Correlation coefficient; Educational institutions; Image edge detection; Image resolution; Remote sensing; Vehicle detection; Vehicles; Vehicle detection; aerial image; correlation coefficient; edge detection; morphological preprocessing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
  • Conference_Location
    Melbourne, VIC
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4799-1114-1
  • Type

    conf

  • DOI
    10.1109/IGARSS.2013.6723710
  • Filename
    6723710