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复杂背景下基于EMDs的运动目标检测

Detection of Moving Object in a Complicated Background Based on EMDs
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摘要 如何快速准确地检测出复杂背景中的运动物体,是图像处理中的一个重要问题。昆虫经长期对自然的适应,能够对视野内的细微运动做出迅速反应,并将目光锁定在运动物体上。初级运动检测模型模拟了蝇的视觉神经处理系统的功能,本文基于该初级运动检测模型,选取一阶无限脉冲响应数字滤波器作为延迟器,增加了高斯差分单元,在提取更多目标细节的同时,去除了信号的随机噪声,为相关模型的计算提供了更多有用的信息。本文基于Matlab软件平台,检测视频中的运动车辆。仿真实验结果表明,该方法不受复杂背景的干扰,精确地提取出运动目标。 How to detect a moving object fast and correctly in a complicated surrounding is one of the most important issues to be solved. Insects could catch a shift in their view field and make an action to prey or flee, which indicates they have peculiar capability to acclimatization. Fly visual system was modeled with an Elementary Motion Detector （EMD）. We chosen first-order IIR digital filter as the time delay unit and made the Difference of Gaussians method to extract more details and eliminate random noise. We carried out simulation experiment based on software Matlab to detect a moving auto. From the result, this method can detect the moving object without the distraction by complicated environment.
作者 许芃 李东光 靳佰良
机构地区 北京理工大学机电动态控制重点实验室 中国人民解放军
出处 《光电工程》 CAS CSCD 北大核心 2013年第8期13-18,共6页 Opto-Electronic Engineering
基金 国防科技重点实验室基金项目资助
关键词 视觉仿生 初级运动检测器 高斯差分 一阶无限脉冲响应数字滤波器 vision bionics elementary motion detectors difference of Gaussians first-order IIR digital filter
分类号 TN911 [电子电信—通信与信息系统]
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参考文献10

  • 1Eichner H, Joesch M, Schnell B, et al. Internal structure of the fly elementary motion detector [J]. Neuron(S0896-6273), 2011, 70(6): 1155-1164.
  • 2Borst A, Euler T. Seeing things in motion: models, circuits, and mechanisms [J]. Neuron(S0896-6273), 2011,71(6): 974-994.
  • 3Rajesh S, O'Carroll D C, Abbott D. Elaborated reichardt correlators for velocity estimation tasks [J]. Proceedings of SPIE(S0277-786X), 2002, 4937: 241-252.
  • 4Zanker J M, Zeil J. Movement-induced motion signal distributions in outdoor scenes [J]. Network: Computation in Neural Systems(S0954-898X), 2005, 16(4): 357-376.
  • 5Reichardt W, EgelhaafM, Guo A. Processing of figure and background motion in the visual system of the fly [J]. Biological cybernetics(S0340-1200), 1989, 61(5): 327-345.
  • 6Van Santen J P, Sperling G. Elaborated reichardt detectors [J]. Journal of the Optical Society of America A(S1084-7529), 1985, 2(2): 300-321.
  • 7李敏,范新南,张学武,张卓,宋凤琴.基于视觉认知机理的复杂动态背景下目标提取[J].光电子．激光,2012,23(2):366-373. 被引量：6
  • 8Guo B. Performance estimation of oversampled bio-inspired velocity estimator based on Reichardt Correlator [D]. Australia: The University of Adelaide, 2010: 43-47.
  • 9王国锋,张科,李言俊.基于初级运动检测器的速度精确估计[J].西北工业大学学报,2003,21(3):306-309. 被引量：3
  • 10YIN Jun, LI Dongguang, FANG Huimin, et al. Moving Objects Detection by Imitating Biologic Vision Based on Fly's Eyes [C]//IEEE International Conference on Robotics and Biomimetics, Shenyang, China, Aug 22-26, 2004: 763-766.

二级参考文献23

  • 1CAI F,CHEN H H, MA J W. Man-made object detection based on texture clustering and geometric structure Fea- ture Extracting[J] Information Technology and Computer Science, 2011,3(2): 9-16.
  • 2ITTI L, KOCH C, NIEBUR E. A model of saliency-based visual attention for rapid scene analysis[J]. IEEE Trans- actions on Pattern Analysis and Machine Intelligence, 1998,20(11) : 1254-1259.
  • 3BRUCE N D B,TSOTSOS J K. Saliency based on infor- mation maximization[J]. Advances in Neural Information Processing Systems, 2006,18 : 155-162.
  • 4WEI S G,CHEN Z, DONG H. Motion detection based on temporal difference method and optical flow field [C]. Second international Symposium on Electronic Commerce and Security ISECS'09,Nanchang: 2009,85-88.
  • 5CHUNG C Y,CHEN H H,et al. Video object extraction via MRF-Based contour tracking[J]. IEEE Circuits and Sys- tems Society,2010,20(1) : 149-155.
  • 6CHEN W H,CHU W T,WU J L. A visual attention based region of interest determination framework for video se- quences[J]. IEICE Transaction on Information and Sys- tems,2005,88(7) : 1578-1586.
  • 7LIU C,YUEN C P,QIU G P. Object motion detection using information theoretic spatial-temporal Saliency[J]. Pat- tern Recognition, 2009,42(11) : 2897-2906.
  • 8ROJER J W, WILLIAM A P. The function of dynamic grouping in vision [J]. Trends in Cognitive Sciences, 2000,4(12) :447-454.
  • 9Reichardt W. Autocorrelation, a principle for the evalua- tion of sensory information by the central nervous system [J]. MIT Press, Cambridge, Mass, 19 61, 11: 513-5 2 4.
  • 10BAYERL P, NEUMANN H. Disambiguating visual motion through contextual feedback modulation[J]. Neural Com- putation, 2004,16(10): 2041-2066.

共引文献7

光电工程
2013年 第8期

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