• DocumentCode
    1858107
  • Title

    Research of Adaptive Frame Difference Moving Target Segmentation Based on MRF

  • Author

    Chen Ge-Heng ; Li Ya-Jing

  • Author_Institution
    Coll. of Comput. Sci. & Eng., Changchun Univ. of Technol., Changchun, China
  • fYear
    2013
  • fDate
    26-28 July 2013
  • Firstpage
    221
  • Lastpage
    224
  • Abstract
    Moving target segmentation which is an important research subject in many fields, such as artificial intelligence, industrial monitoring and human-computer interaction, the research of moving target segmentation algorithm in video sequence has vital academic significance and practical value. This paper introduced Markov Random Field theory into image sequence target segmentation process which is based on initial segmentation in static scene. In the paper, we constructed Adaptive Markov Random Field algorithm combining with adaptive Otsu method, namely the AMRF model. And also extracted the inter-frame difference mask by this model and inter-frame difference method. Experimental results show that the algorithm is effective and the moving target segmentation effect by this model is desirable.
  • Keywords
    Markov processes; feature extraction; image segmentation; image sequences; random processes; video signal processing; AMRF model; Markov random field theory; adaptive Markov random field algorithm; adaptive Otsu method; artificial intelligence; human-computer interaction; image sequence target segmentation process; industrial monitoring; inter-frame difference mask; inter-frame difference method; moving target segmentation; static scene segmentation; video sequence; Adaptation models; Computational modeling; Educational institutions; Image segmentation; Markov random fields; Mathematical model; Probability distribution; MRF; frame difference; segmentation; target;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Graphics (ICIG), 2013 Seventh International Conference on
  • Conference_Location
    Qingdao
  • Type

    conf

  • DOI
    10.1109/ICIG.2013.50
  • Filename
    6643669