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基于伪Zernike矩不变量分析的视觉测力 被引量:4

Visual Force Measurement Using Pseudo Zernike Moment Invariants
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摘要 提出了一种基于伪Zernike矩不变量分析的视觉测力方法.该方法利用伪Zernike矩不变量所构成的特征向量来描述微装配过程中微夹爪变形之后的形状,并由此建立了矩不变量特征向量与受力之间的函数关系;建立训练集,输入为矩不变量特征向量,输出为已知受力;通过支持向量机比较测试集与训练集中的特征向量,对测试集的输入进行多类分类,从而估计未知受力.对4种不同规格的微悬臂梁进行了实验,结果验证了该方法的有效性. A new visual force measurement method was proposed to measure applied forces through analyzing pseudo Zernike moment invariants. First, a feature vector of pseudo Zernike moment invariants is used to describe the deformed microgripper shape in microassembly. This description indicates a function between the applied force and the feature vector of moment invariants. Then, a training set is established, where the input and the output represent the feature vector of moment invariants and the corresponding known applied force, respectively. Finally, a support vector machine (SVM) compares the feature vectors in the testing set with those ones in the training set, implements multi-class classification and estimates unknown applied forces in the testing set. The experiments on four different microcantilevers validate the proposed method.
出处 《上海交通大学学报》 EI CAS CSCD 北大核心 2013年第4期589-593,共5页 Journal of Shanghai Jiaotong University
基金 国家自然科学基金资助项目(50875169)
关键词 视觉测力 伪Zernike矩不变量 支持向量机 多类分类 visual force measurement pseudo Zernike moment invariants support vector machine multiclass classification
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  • 1Reddy A N, Ananthasuresh G K. On computing forces from the noisy displacement data of an elastic body [J]. International Journal for Numerical Meth- ods in Engineering, 2008, 76(11): 1645-1677.
  • 2Reddy A N, Maheshwari N, Sahu D K, eta[. Mini- ature compliant grippers with vision-based force sens- ing [J]. 1EEE Transactions on Robotics, 2010, 26 (5) : 867-877.
  • 3Wang X, Ananthasuresh G K, Ostrowski J P. Vi- sion-based sensing of forces in elastic objects [J]. Sensors and Actuators, 2001, 94(3) : 142-156.
  • 4Greminger M A, Nelson B J. Vision-based forcemeasurement [J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(3): 290 298.
  • 5Anis Y H, Mills J K, Cleghorn W L. Vision-based measurement of mieroassembly forces [J]. Journal of Micromechanics and Microengineering, 2006, 16 (8) : 1659-1652.
  • 6Mukundan R, Ramakrishnan K R. Moment functions in image analysis: Theory and applications [M]. Sin- gapore: Word Scientific Publishing, 1998.
  • 7Ye B, Peng J. Invariance analysis of improved Zerni- ke moments [J]. Journal of Optics A: Pure and Ap- plied Optics, 2002, 4(6): 606-614.
  • 8Papakostas G A, Boutalis Y S, Karras I) A, et a[. Efficient computation of Zernike and pseudo-Zernike monclents for pattern classification applications [J]. Pattern Recognition and Image Analysis, 2010, 20 (1) : 55 64.
  • 9A1-Raw M S. Fast computation of pseudo Zernike moments [J]. Journal of Real-Time Image Processing, 2010, 5(1): 3-10.
  • 10丁世飞,齐丙娟,谭红艳.支持向量机理论与算法研究综述[J].电子科技大学学报,2011,40(1):2-10. 被引量:871

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同被引文献26

  • 1张平定,孙佳佳,童创明,季明阳,张鸣鸣.弹道中段目标雷达综合识别研究[J].微波学报,2015,31(2):20-23. 被引量:14
  • 2徐建斌,洪文,吴一戎.一种基于Zernike矩和稳态遗传算法的遥感图像匹配方法[J].电子与信息学报,2005,27(6):924-927. 被引量:4
  • 3Zernike F. Beugungstheorie des schneidenver -fahrens und seiner verbesserten form, der phasenkontrastmethode [ J ]. Physica, 1934, 1(7): 689-704.
  • 4Khotanzad A, Hong Y H. Invariant image recognition by Zernike moments[ J]. Pattern Analysis and Machine Intelli- gence, IEEE Transactions on, 1990, 12(5) : 489 -497.
  • 5Hosny K M, Papakostas G A, Koulouriotis D E. Accurate reconstruction of noisy medical images using orthogonal mo- ments[C]//Digital Signal Processing (DSP), 2013 18th International Conference on. IEEE, 2013 : 1 -6.
  • 6Kulkami A H, Rai H M, Jahagirdar K A, et al. A Leaf Recognition System for Classifying Plants Using RBPNN and pseudo Zernike Moments [ J ]. International Journal of Latest Trends in Engineering and Technology, 2013, 2( 1 ) : 6 -10.
  • 7Salouan R, Safi S, Bouikhalene B. A Comparative Study between the Pseudo Zernike and Krawtchouk Invariants Mo- ments for Printed Arabic Characters Recognition[ J ]. Jour- nal of Emerging Technologies in Web Intelligence, 2014, 6 (1):1 -7.
  • 8Khotanzad A, Hong Y H. Invariant image recognition by Zernike moments [ J ]. Pattern Analysis and Machine Intelli- gence, IEEE Transactions on, 1990, 12(5) : 489 -497.
  • 9Cortes C, Vapnik V. Support-vector networks [ J ]. Ma- chine learning, 1995, 20(3) : 273 -297.
  • 10Teh C H, Chin R T. On image analysis by the methods of moments [ J ]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1988, 10(4) : 496 -513.

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