期刊文献+

视频检测系统中的背景更新算法研究 被引量:1

A Study on Background Updating Used in Video Detection System
下载PDF
导出
摘要 实际场景中环境是动态变化的,如灯光或太阳光产生的亮、暗变化以及由于太阳光照射角度产生的阴影位置变化等情况。需要对背景进行实时更新。为此,提出了一种基于分块的无初始背景约束的更新方法。算法在一定时间内根据块匹配判断该块是否处于稳定状态,进而利用块的均值和方差决定此块是否处于连续的稳定状态,从而判定该块是否需要更新。算法通过现场数据实验,包括隧道中车流量较小的、隧道中车流量较大的、隧道出口光线变化剧烈的、隧道出口阴影位置变化等环境,结果表明在各种环境下背景更新都有较好的效果。 Changes of environment is dynamic,such as light,the sun light and shadow area under different reflections.In these conditions it needs real-time background updating.This paper presents a method of background updating based on block.Algorithm is done according to the block matching in stable condition in a certain period,then use block mean and variance to decide whether this block in the continuous stable state,and decide whether the block need updating,through a lot of experiments,including the condition in the tunnel,the light changes in the tunnel and the shadow position changes,etc.The results indicate that background updating have better effect.
作者 苏书杰
出处 《商洛学院学报》 2011年第4期30-33,共4页 Journal of Shangluo University
关键词 智能交通系统 图像处理 分块 背景更新 intelligent transportation system image processing block background updating
  • 相关文献

参考文献4

二级参考文献47

  • 1Nariman,H.,Alirem,M.,Neil,B.:Automatic Thresholding for Change Detection in Digital Video.in Proe.SPIE.4067(2000)133—142.
  • 2C E Daniell, D J Kemsley, W P Lincoln, et al. Artificial neural networks for automatic target recognition[J]. Opt Eng,1992,31(12):2521-2530.
  • 3S K Rogers, J M Colombi, C E Martin, et al. Neural networks for automatic target recognition[J]. Neural Networks, 1995,18(7/8):1153-1184.
  • 4W A Thoet, T G Rainey, D W Brettle,et al. ANVIL neural network program for three-dimensional automatic target recognition[J]. Opt Eng, 1992,31(12).
  • 5Alan J Lipton, H Fujiyoshi, Raju S Patil. Moving target classification and tracking from real-time video[J]. IEEE Transactions on Workshop Application of Computer Vision, 1998, 8-14.
  • 6Alireza Behrad, Ali Shahrokni, Seyed Ahmad Motamedi. A robust vision-based moving target detection and tracking system[EB/OL]. http:∥ligwww.epfl.ch/~ali.
  • 7Jaewon Shin. Initialization of visual object tracker using frame absolute difference[EB/OL]. http:∥ise.stanford.edu/class/ee392j/projects/shin-report.pdf.
  • 8Paul L Rosin, Tim Ellis. Image difference threshold strategies and shadow detection[EB/OL]. http:∥www.cs.cf.ac.uk/User/Paul.Rosin/resources/papers/shadows.pdf.
  • 9Shoichi Araki, Takashi Matsuoaka, Naokazu Yokoya, et al. Real-time tracking of multiple moving object contours in a moving camera image sequence[J]. IEICE Trans Inf & Syst, 2000,E83-D(7).
  • 10Jain R, Nagel H. On the analysis of accumulative difference of picture from image sequences of real world scenes[J]. IEEE Transactions PAMI, 1979. 206-214.

共引文献71

同被引文献12

引证文献1

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部