Laser & Optoelectronics Progress, Volume. 55, Issue 5, 051001(2018)

Digital Speckle Correlation Method Based on Improved Curved Surface Fitting Method

Kaiqiang Li1,2,3,4、1; 2; 3; 4, Dan Zhu1,2,3,4、1; 2; 3; 4, and Xinxin Tong1,2,3、1; 3; 4;
Author Affiliations
  • 1 Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 2 Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 2 University of Chinese Academy of Sciences, Beijing 100049, China
  • 3 Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 3 Liaoning Provincial Key Laboratory of Image Understanding and Computer Vision, Shenyang, Liaoning 110016, China
  • 4 Liaoning Provincial Key Laboratory of Image Understanding and Computer Vision, Shenyang, Liaoning 110016, China
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    The digital speckle correlation method based on bivariate quadratic polynomial curved surface fitting method for precise sub-pixel localization has the advantages of simple calculation and high efficiency. The original method usually selects nine pixels around the integer pixel for surface fitting. We use the nearest six pixels around the integer pixel and the correlation coefficient to directly solve the bivariate quadratic polynomial through analyzing the possible improvement schemes of surface fitting. The speckle patterns are generated by computer simulation, as well as the rigid body translation experiments and uniaxial tension experiments are simulated respectively. Experimental results show that the improved scheme has the advantages of high computational efficiency and small computational error.

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    Kaiqiang Li, Dan Zhu, Xinxin Tong. Digital Speckle Correlation Method Based on Improved Curved Surface Fitting Method[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051001

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    Paper Information

    Category: Image processing

    Received: Oct. 17, 2017

    Accepted: --

    Published Online: Sep. 11, 2018

    The Author Email: Li Kaiqiang (likaiqiang@sia.cn)

    DOI:10.3788/LOP55.051001

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