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文章基本信息

  • 标题:Moving Object Detection Research Based on Background Image Set and Sparse Analysis
  • 本地全文:下载
  • 作者:Huang Ke
  • 期刊名称:Journal of Software Engineering
  • 印刷版ISSN:1819-4311
  • 电子版ISSN:2152-0941
  • 出版年度:2016
  • 卷号:10
  • 期号:1
  • 页码:66-77
  • DOI:10.3923/jse.2016.66.77
  • 出版社:Academic Journals Inc., USA
  • 摘要:A moving target detection method is proposed based on the background image set and sparse representation in this stduy. The method combined the Robust Principal Component Analysis (RPCA) and the image block analysis method based on sparse representation. The authors got a series of background images from a video sequence by RPCA and combined these background images as the background image set, treating image block as basic unit and moving target was extracted from input frame by image block analysis method based on sparse representation. The simulation results indicate that when the background illumination mutates, the proposed method can effectively eliminate the impact of environment noise and reduce the false detection rate of target detection.
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