首页    期刊浏览 2025年06月15日 星期日
登录注册

文章基本信息

  • 标题:Salient Approach for Motion Detection in Real Time Domain
  • 本地全文:下载
  • 作者:Girish Kapse ; Akash Bisht ; Parul Upadhyay
  • 期刊名称:International Journal of Innovative Research in Science, Engineering and Technology
  • 印刷版ISSN:2347-6710
  • 电子版ISSN:2319-8753
  • 出版年度:2017
  • 卷号:6
  • 期号:4
  • 页码:5866
  • DOI:10.15680/IJIRSET.2017.0604201
  • 出版社:S&S Publications
  • 摘要:In today’s world CCTV’s are being invested in almost every place be it shopping complex, hospitals,schools or someone’s home. It helps in recording any apprehensive activity taking place, but the most importantinconvenience of CCTV cameras is that it records for the entire time, the moment it is enabled. This process misspendsa lot of memory since the camera is on unnecessarily moreover CCTV camera does not have an alarming system bywhich whenever there is any dubious activity it can alert the possessor. Therefore, there is a necessity of a system inwhich the camera will record only when there is a motion in the frame of the camera. For this an innovative real time,based algorithm is effectuated which uses various methods to detect motion in real time domain and enable the camerato record whenever there is a motion hence reducing memory wastage. This algorithm incorporates the temporaldifferencing method, optical flow method, double background filtering, morphological processing method to attainoptimal performance. The most exceptional advantage of this method is that the it does not need to have the knowledgeabout the background model from thousands of images and it can handle immediate changes in the image withoutpreexisting knowledge of the shape and size of the object. This method also takes less guesstimation time as comparedto the diverse real time based motion detection algorithms available. The algorithm is enforced in a simulationenvironment and theproductiveness of this method is indicated in this paper. The evaluation results are proclaimed inthis paper.
  • 关键词:Temporal Difference; Double Background Filtering; Optical Flow; Morphological Processing
国家哲学社会科学文献中心版权所有