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一种基于自适应域值混合差分的目标检测方法 被引量:2

A TARGET DETECTION METHOD BASED ON ADAPTIVE THRESHOLD MIXED DIFFERENCE
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摘要 基于视频的目标检测中,现有流行的高斯混合模型GMM(Gaussian Mixture Model)目标检测的效果最好,但是其计算量很大,而简单的帧间差分方法和背景差分方法计算速度快,但是检测效果较差。提出在改进聚类方法基础上的基于自适应域值混合差分的目标检测方法,能够一方面具有很好的运动目标检测效果,另一方面具有很快的计算处理速度。同时该方法具有自适应能力,免除人工设置域值的麻烦,因而在实践中具有良好的实际使用价值。 In target detecting methods based on video processing technology, GMM ( Gaussian Mixture Model) is today' s popular way with highest detecting effect but is time-consuming in computation. Meanwhile those methods such as inter-frame difference and background difference are simple and quick in computation but with poorer detection qualityIn this paper,we proposed a target detection method based on adaptive threshold mixed difference with the improved OpenCV clustering algorithm. The method was proved to have perfect detection effect on mo- tion targets and fast computing speed. Besides, it was also adaptive in getting rid of threshold manual setting, thus had the practical applied value in engineering.
出处 《计算机应用与软件》 CSCD 2009年第10期94-97,共4页 Computer Applications and Software
基金 广东省科技计划项目(2006B11301001) 广东省国际科技合作计划项目(2007A050100026) 广东省工业科技攻关计划项目(2006B80407001)
关键词 目标检测 高斯混合模型 背景差分 混合差分 自适应域值 Target detection Gaussian mixture model Background difference Mixed difference Adaptive threshold
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  • 1傅德胜,王海彬,孙文静.数字视频监控中的运动目标检测[J].微电子学与计算机,2005,22(1):118-121. 被引量:16
  • 2赵鹏,浦昭邦,张田文.一种新的红外与可见光图像融合与跟踪方法[J].光电工程,2005,32(2):37-40. 被引量:18
  • 3姚敏.数字图像处理[M].北京:机械工业出版社,2008.
  • 4Meier T, Ngun K N. Video segmentation for content-- based coding[J]. IEEE Trans on Circuits and Systems for Video Technology, 1999, 9(8) : 1190- 1203.
  • 5Gupt S, Masound O, Martin R F K, et al. Detection and classification for vechicles[J]. IEEE Transcations on Intelligent Transportation Systems, 2002, 3 (1) : 37 -47.
  • 6Dyana A, Subramanian M P, Das S. Combining features for shape and motion trajectory of video objects for effi- cient content based video retrieval[C]//Seventh Inter-national Conference on Advances in Pattern Recogni- tion. kolkata: IEEE, 2009 : 113- 116.
  • 7Chaisorn L, Manders C, Rahardja S. Video retrieval-- evolution of video segmentation, indexing and search [C]//proceedings of the 2nd IEEE Internation Confer- ence on Computer Science and Information Technology. Beijing, China~ IEEE, 2009 .. 16-20.
  • 8Tahayna B, Belkhatir M, alhashmi S. Motion informa- tion for video retrieval[C]//IEEE International Confer- ence on Multimedia and Expo, New, York, NY:IEEE, 2009.. 870-873.
  • 9Burt P J, Andelson E H. The Laplacian pyramid as a compact im- age code [J]. IEEETrans. Commun, 1983, 31 (4): 532-540.
  • 10Mukhopadhyay S, Chanda B. Fusion of 2D gray scale images using mul- tiscale morphology [J]. Pattern Recog, 2001, 34 (10): 1939 - 1949.

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