• DocumentCode
    3577965
  • Title

    Robust vehicle detection and tracking method for Blind Spot Detection System by using vision sensors

  • Author

    Seunghwan Baek ; Heungseob Kim ; Kwangsuck Boo

  • Author_Institution
    High Safety Vehicle Core Technol. Res. Center, Inje Univ., Gimhae, South Korea
  • fYear
    2014
  • Firstpage
    729
  • Lastpage
    735
  • Abstract
    This paper presents a method to detect the present vehicles from side and rear for BSDS(Blind Spot Detection System) with vision system. Because the real image acquired during car driving has a lot of information to exam the target vehicle, background image, and the noises such as lighting and shading, it is hard to extract only the target vehicle for the background image with satisfied robustness. In this paper, the target vehicle is detected by repetitive image processing such as sobel and morphological operations and a Kalman filter is also designed to cancel the background image and prevent the misreading of the target image. Compared to previous researches, the proposed method can get an image processing with much improved speed and robustness. Various experiments were performed on the highway driving situations to evaluate the performance of the proposed algorithm.
  • Keywords
    Kalman filters; automobiles; computer vision; image sensors; object detection; object tracking; traffic engineering computing; BSDS; Kalman filter; background image; blind spot detection system; car driving; highway driving situations; image processing; morphological operations; repetitive image processing; robust vehicle detection; robust vehicle tracking method; satisfied robustness; sobel operations; target vehicle; vision sensors; Computational modeling; Image resolution; Kalman filters; Robustness; Vehicles; Blind Spot Detection System(BSDS); Collision Prevention; Kalman Filter; Lane Change Assist(LCA); Vehicle Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Complex Systems (WCCS), 2014 Second World Conference on
  • Print_ISBN
    978-1-4799-4648-8
  • Type

    conf

  • DOI
    10.1109/ICoCS.2014.7060984
  • Filename
    7060984