• DocumentCode
    2710672
  • Title

    Frame Based Object Detection--An Application for Traffic Monitoring

  • Author

    Low, Chin Hong ; Lee, Ming Kiat ; Khor, Siak Wang

  • Author_Institution
    Fac. of Inf. & Commun. Technol., Univ. Tunku Abdul Rahman, Petaling Jaya, Malaysia
  • fYear
    2010
  • fDate
    7-10 May 2010
  • Firstpage
    322
  • Lastpage
    325
  • Abstract
    In this paper, we describe a system that is capable of detecting and segmenting objects from video frames which helps in traffic surveillance. Shadow is one of the problems faced by most of the object detection systems. It will affect the result of object detection and segmentation. Hence a shadow removal method is applied in the preprocessing phase of the system to amplify the accuracy of detection. MATLAB is the major platform for developing this system. By differentiating the background and foreground of the video scenes using MATLAB embedded functions, the foreground regions are segmented as the objects. The segmented objects are saved for further development of computer vision applications such as object recognition and classification. The proposed system is tested with four traffic video scenes and the experimental results show that the system works well with an accuracy of approximately 90% achieved.
  • Keywords
    image segmentation; object detection; traffic engineering computing; video surveillance; MATLAB; computer vision applications; frame based object detection; object segmentation; traffic surveillance; video frames; Application software; Computer vision; Face detection; Layout; MATLAB; Monitoring; Object detection; Object recognition; Phase detection; Surveillance; background subtraction; object detection; object segmentation; shadow removal; surveillance; traffic flow monitoring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Research and Development, 2010 Second International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-0-7695-4043-6
  • Type

    conf

  • DOI
    10.1109/ICCRD.2010.63
  • Filename
    5489557