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  • 标题:An Improved Moving Object Detection Algorithm Based on Gaussian Mixture Models
  • 本地全文:下载
  • 作者:Xuegang Hu ; Jiamin Zheng
  • 期刊名称:Open Journal of Applied Sciences
  • 印刷版ISSN:2165-3917
  • 电子版ISSN:2165-3925
  • 出版年度:2016
  • 卷号:06
  • 期号:07
  • 页码:449-456
  • DOI:10.4236/ojapps.2016.67045
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:Aiming at the problems that the classical Gaussian mixture model is unable to detect the complete moving object, and is sensitive to the light mutation scenes and so on, an improved algorithm is proposed for moving object detection based on Gaussian mixture model and three-frame difference method. In the process of extracting the moving region, the improved three-frame difference method uses the dynamic segmentation threshold and edge detection technology, and it is first used to solve the problems such as the illumination mutation and the discontinuity of the target edge. Then, a new adaptive selection strategy of the number of Gaussian distributions is introduced to reduce the processing time and improve accuracy of detection. Finally, HSV color space is used to remove shadow regions, and the whole moving object is detected. Experimental results show that the proposed algorithm can detect moving objects in various situations effectively.
  • 关键词:Moving Object Detection;Gaussian Mixture Model;Three-Frame Difference Method;Edge Detection;HSV Color Space
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