• DocumentCode
    1933531
  • Title

    Automatic Moving Object Segmentation Based on HOS and An Improved Active Contour

  • Author

    Zhang, Xiaoyan ; Xia, Jingbo ; Ma, Zhiqiang

  • Author_Institution
    Inst. of Telecommun. Eng., Air Force Eng. Univ., Xi´´an
  • Volume
    2
  • fYear
    2006
  • fDate
    16-20 2006
  • Abstract
    A novel algorithm for automatic moving object segmentation is proposed in this paper. The proposed segmentation system includes two main modules, moving object model locating and contour correction. In the former module, HOS (higher-order statistics) is used to automatically separate the moving areas from the background. Then the morphological filter is used to remove the noises and holes. Based on the intersection operation of the two moving areas which obtained from three successive frames, the occlude background may be removed and moving object model can be obtained. However, the result of the previous process fails to obtain the accurate moving object contour. To solve this problem, the initial contour of the moving object is extracted and an improved active contour which uses the gradient vector as the external force guides the initial contour moving to the actual video object contour. Experiment results testify that the proposed algorithm is of few parameters, robust to noise and best in result of segmentation
  • Keywords
    filtering theory; higher order statistics; image denoising; image morphing; image segmentation; active contour; automatic moving object segmentation; contour correction; gradient vector; higher-order statistics; morphological filter; moving object extraction; moving object model; Active contours; Application software; Computer vision; Convergence; Filters; Higher order statistics; Image processing; Image segmentation; Object segmentation; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2006 8th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9736-3
  • Electronic_ISBN
    0-7803-9736-3
  • Type

    conf

  • DOI
    10.1109/ICOSP.2006.345702
  • Filename
    4128994