• DocumentCode
    2898607
  • Title

    Automatic Video Object Segmentation using Wavelet Transform and Moving Edge Detection

  • Author

    Zhang, Xiao-yan ; Zhao, Rong-chun

  • Author_Institution
    Coll. of Comput., Northwestern Polytech. Univ., Xi´´an
  • fYear
    2006
  • fDate
    13-16 Aug. 2006
  • Firstpage
    3929
  • Lastpage
    3933
  • Abstract
    A fast and automatic video object segmentation algorithm based on wavelet transform and moving edge detection is proposed in this paper. First, the wavelet transform is applied to two consecutive frames. The change detection method with different thresholds in four wavelet sub-bands and Canny edge detection are used in wavelet domain. After the inverse wavelet transform, the robust difference edge map can be obtained. Through combination with the current frame edge map, background edge map and previous frame´s moving edge, the current frame´s moving edge can be detected and tracked. It is then used to extract video object plane (VOP) by a simple filling technique. The proposed algorithm is robust to the entire motion and local deformation of object. Experiments results and object evaluation demonstrate the effectiveness of our algorithm
  • Keywords
    edge detection; image segmentation; object detection; video coding; wavelet transforms; Canny edge detection; automatic video object segmentation; change detection method; edge map; inverse wavelet transform; moving edge detection; object deformation; video object plane; wavelet subbands; Change detection algorithms; Cybernetics; Image edge detection; Image segmentation; Low pass filters; Machine learning; Object detection; Object segmentation; Partitioning algorithms; Robustness; Wavelet domain; Wavelet transforms; Binary edge model; Change detection; Video object; Video object plane (VOP); Wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2006 International Conference on
  • Conference_Location
    Dalian, China
  • Print_ISBN
    1-4244-0061-9
  • Type

    conf

  • DOI
    10.1109/ICMLC.2006.258748
  • Filename
    4028757