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光电跟踪中实时视频对象分割算法

An Algorithm of Video Object Segmentation in Real-Time in Electric-Optic Tracking
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摘要 光电跟踪系统研究中难点的问题是实时跟踪目标。针对光电跟踪系统所跟踪的空中目标在视频序列中的特性,将整个跟踪过程划分为远距离段、航前(后)段、航捷段。然后对远距离航段,采取一种弱小目标的动态规划检测算法,及时发现并跟踪目标;在航前(后)段,采取一种基于自适应双波门的视频对象分割算法分割出运动目标,计算出目标形心与跟踪物镜的角偏差,以偏差作为光电跟踪伺服系统的输入信号,驱动跟踪器跟踪目标;在航捷段,将每帧视频变换为一组分辨率从高到低类似金字塔式的分层框架,对目标采取从粗到细的方式进行分割,以实现视频对象占据大部分视窗时的目标快速、准确分割。通过实例验证了所提出的算法的有效性。 One of the hotspot and difficult subjects in electric-optic tracking systems is to segment video object accurately in real time. First,under the consideration of the characteristics of targets of electric-optic tracking systems in video sequences,the whole tracking process is divided into the remote section of track,the front (rear) of track and the course short of track. Second,a dynamic programming algorithm is used to detect small targets in the remote section of track,which can help electric-optic tracking systems to find and track small targets. Then,on the basis of adaptive double windows,an algorithm of video object segmentation is used to segment motion targets in the front (rear) of track and the angle deviations between the centroid of targets and the tracking lens,which are the input signals of the servo control system of electric-optic tracking system,and can be computed and used to drive the tracking device to track the target. In the course short of track,each video frame is transferred into a group of frames from high resolution to low resolution,like a pyramid layered framework. And then the video object is segmented in terms of an approach from rough segmentation to delicate segmentation such that the object can be fast and accurately segmented when video object occupies a majority of the screen of electric-optic tracking system. Finally,experiment simulation results demonstrate the valid of the proposed algorithm.
出处 《计算机仿真》 CSCD 北大核心 2010年第9期230-234,322,共6页 Computer Simulation
基金 国家自然科学基金资助项目(60804019) 江苏省博士后基金资助项目(0701022C)
关键词 视频对象分割 视频对象跟踪 自适应双波门 光电跟踪 Video object segmentation Video object tracking Adaptive double window Electric-optic tracking
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参考文献10

  • 1侯志强,韩崇昭.视觉跟踪技术综述[J].自动化学报,2006,32(4):603-617. 被引量:254
  • 2A F Smeato.Techniques used and open challenges to the analysis,indexing and retrieval of digital video[J].Information Systems,2007,32(4):545-559.
  • 3E Trucco,K Plakas.Video tracking:A concise survey[J].IEEE Journal of Oceanic Engineering,2006,31(2):520-529.
  • 4张然,吕高杰,张国华.光电目标图像自动跟踪技术研究[J].电光与控制,2008,15(9):65-68. 被引量:8
  • 5丁一,毛征,雷加印,卢青山.一种自适应双波门电视跟踪算法[J].火炮发射与控制学报,2007,28(1):44-46. 被引量:5
  • 6S MTonissen,R J Evans.Performance of dynamic programming techniques for track-before-detect[J].IEEE Transactions on Aerospace and Electronic Systems,1996,32(4):1440-1451.
  • 7L A Johnston,V Krishnamurthy.Performance analysis of a track before detect dynamic programming algorithm[C].Silver Anniversary IEEE International Conference on Acoustics,Speech,and Signal Processing,Istanbul,Turkey:ICASSP 2000.49-52.
  • 8L A Johnston,V Krishnamurthy.Performance analysis of a dynamic programming track before detect algorithm[J].IEEE Transactions on Aerospace and Electronic Systems,2002,38(1):228-242.
  • 9T Kirishima,K Sato,K Chihara.Real-time gesture recognition by learning and selective control of visual interest points[J].IEEE Transaction on Pattern Analysis Machine Intelligence,2005,27(3):351-364.
  • 10朱磊,徐佩霞,何佳.基于自适应邻域概念的实时视频预处理算法[J].中国科学技术大学学报,2005,35(2):154-160. 被引量:2

二级参考文献22

  • 1王东升,李在铭.空域视频场景监视中运动对象的实时检测与跟踪技术[J].信号处理,2005,21(2):195-198. 被引量:5
  • 2马奔,史忠科,皮燕妮.成像目标跟踪算法分析[J].西安电子科技大学学报,2005,32(3):477-480. 被引量:11
  • 3侯志强,韩崇昭.基于像素灰度归类的背景重构算法[J].软件学报,2005,16(9):1568-1576. 被引量:97
  • 4邵文坤,黄爱民,韦庆.目标跟踪方法综述[J].影像技术,2006,18(1):17-20. 被引量:24
  • 5Gonzalez R C, Woods R E. Digital Image Proeessing[M]. New York: Addison Wesley, 1992.
  • 6Milan Sonka, Vaclav Hlavac, Roger Boyle.Image Processing, Analysis, and Machine Vision, Second Edition[M]. California:Brooks Cole, 1998.
  • 7Ciuc M, Rangayyan R M, Zaharia T, et al.Filtering noise in color images using adaptive neighoborhood statistics[J]. Journal of Electronic Imaging, 2000, 9(4);484-494.
  • 8Rangayyan R M,Das A. Filtering multiplicative noise in images using adaptive region-based statistics[J]. Journal of Electronic Imaging, 1998, 7(1);222-230.
  • 9Pitas I, Venetsanopoulos A N. Order statistics in digital image processing[A]. Proceed-ing of IEEE 80[C]. 1992:1 893-1 923.
  • 10Astola J, Haavisto P, Neuvo Y. Vector median filter[A]. Proceeding of IEEE 78[C].1990 : 678-689.

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