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文章基本信息

  • 标题:Real Time Vehicle Detection and Counting Method for Unsupervised Traffic Video on Highways
  • 作者:P.M.Daigavane ; P.R.Bajaj
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2010
  • 卷号:10
  • 期号:8
  • 页码:112-117
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:Automatic detecting and counting vehicles in unsupervised video on highways is a very challenging problem in computer vision with important practical applications such as to monitor activities at traffic intersections for detecting congestions, and then predict the traffic flow which assists in regulating traffic. Manually reviewing the large amount of data they generate is often impractical. The background subtraction and image segmentation based on morphological transformation for tracking and counting vehicles on highways is proposed. This algorithm uses erosion followed by dilation on various frames. Proposed algorithm segments the image by preserving important edges which improves the adaptive background mixture model and makes the system learn faster and more accurately, as well as adapt effectively to changing environments.
  • 关键词:Vehicle detection; background subtraction; morphological operator; traffic analysis
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