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灰度图像序列中运动目标提取方法的研究 被引量：2

Research on Selecting Kinematic Objects from Tonal - gradation Image series
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摘要 随着人们对运动图像研究的深入,运动检测及提取算法的研究也在不断的发展。该文给出了一种从灰度图像序列中提取运动目标的算法——模板对准相乘法。实验证明,该种算法提取出的运动目标失真度小,误检率低,性能比常用的差值法和符号判别法要明显地优越。 The algorithm of kinematic detecting and selecting evolves along with the research on kinematic irnages. A new algorithm, namely,mold - plate - comparing, airning at selecting kinematic images from tonal - gradation imag-es, is to be advanced in this thesis, which proves to have low degree of distortion and little false - detecting probability and enjoy more advantages than traditional algorithm, D - value and symbol discrimation.
作者 易国华
机构地区 江汉石油学院电子与信息工程系
出处 《鄂州大学学报》 2003年第4期25-27,共3页 Journal of Ezhou University
关键词 灰度图像序列 运动目标 提取方法 模板对准相乘法 失真度 误检率 图像识别 运动检测 image,data processing kinematic detecting pattern recognition
分类号 TN911.73 [电子电信—通信与信息系统]
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参考文献1

  • 1[2]周新伦,柳健,刘华志.数字图像处理.北京:国防工业出版社,1986

同被引文献16

  • 1SSVM&colon,A Smooth support vector Machine for Classification Lee,Yuh-Jye,Mangasarian,O.L,Computational Optimization and Applications,2001,Vol.20,No.1,5-22
  • 2András,Péter,The Equivalence of support vector Machine and Regularization Neural Networks,Neural Processing Letters,2002,2,97-104
  • 3DAVID M.J.TAX,ROBERT P.W.DUIN,Support Vector Data Description,Machine Learning,2004,54,45-66
  • 4Lee Yuh-Jye,Mangasarian O L.A smooth support vector machine for classification[J].Computational Optimization and Applications,2001,20 (1):5-22.
  • 5András Péter.The equivalence of support vector machine and regularization neural networks[J].Neural Processing Letters,2002,15(2):97-104.
  • 6Zhou Ye,Starkey J,Mansinha L.Segmentation of petrographic images by integrating edge detection and region growing[M].[S.l.]:Computers & Geosciences,2004.
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  • 9Fukunaga K.Introduction to statistical pattern recognition[M].New York:Academic Press,1990.
  • 10Tax D M J,Duin R P W.Support vector data description[J].Machine Learning,2004,54:45-66.

引证文献2

二级引证文献1

鄂州大学学报
2003年 第4期

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