Laser & Optoelectronics Progress, Volume. 56, Issue 7, 071202(2019)

Performance Analysis of Three-Dimensional Measurement Algorithm with Focus Variation Microscopic Imaging

Yanqiong Shi1、**, Qiuxia Ying2, and Rongsheng Lu2、*
Author Affiliations
  • 1 School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei, Anhui 230601, China
  • 2 School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Hefei, Anhui 230009, China
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    Figures & Tables(16)
    Schematic of focus variation
    Ideal focusing curve
    An experimental image obtained using focus variation microscopy and three testing points
    Focus curves obtained from single point information and neighborhood information with different operators. (a) Brenner operator; (b) Roberts operator; (c) Laplace operator; (d) Tenengrad operator; (e) SMD operator; (f) gradient square; (g) Sobel operator in eight directions
    Focus scatter plots with different sizes of neighborhood. (a) 5; (b) 9; (c)13; (d) 17
    Focusing evaluation results of points with different brightness. (a) (380,280); (b) (700,390); (c) (608,218)
    Focusing evaluation results of three brighter points. (a) (765,115); (b) (363,1095); (c) (829,68)
    Schematic of wavelet fusion method
    Comparison of image fusion results. (a) Image fusion based on spatial regional characteristics; (b) image fusion with frequency domain wavelet; (c) color image fusion with frequency domain wavelet
    Experimental system
    Image sequence diagrams of coin surface. (a) 1st image; (b) 2nd image; (c) 30th image; (d) 31st image; (e) 80th image; (f) 81st image
    3D measurement results of coin surface relief. (a) 3D point cloud; (b) 3D color reconstruction image
    A gauge step measurement result. (a) One of images in image sequence; (b) 3D point cloud data; (c) point cloud distribution of a section
    • Table 1. Time consumed per image during focus evaluation by using single point and neighborhood information

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      Table 1. Time consumed per image during focus evaluation by using single point and neighborhood information

      OperatorTime /s
      Single pointNeighborhood
      Brenner0.132.58
      Roberts1.583.24
      Laplace1.813.40
      Tenengrad0.312.70
      SMD0.162.58
      Gradient square0.162.59
      Sobel operator in eight directions10.814.12
    • Table 2. Time consumed per image during focus evaluation with different sizes of neighborhood

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      Table 2. Time consumed per image during focus evaluation with different sizes of neighborhood

      Neighborhood size /pixelTime /s
      52.31
      92.37
      132.44
      172.57
    • Table 3. Comparison of results obtained by different extremum searching methods

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      Table 3. Comparison of results obtained by different extremum searching methods

      PointcoordinatesTraversalsearchTwo polynomialfittingGaussianfittingMaximum valuequadratic fittingMaximum valueGaussian fittingMaximum valueRANSAC
      (380,280)4846.2947.8648.2348.4048.10
      (700,390)4949.5048.4748.9348.8948.93
      (608,218)5047.5250.8349.5949.5249.33
      (363,1095)4683.6744.4845.7745.5945.79
      (829,68)749.7823.8574.2374.4274.26
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    Yanqiong Shi, Qiuxia Ying, Rongsheng Lu. Performance Analysis of Three-Dimensional Measurement Algorithm with Focus Variation Microscopic Imaging[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071202

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Aug. 6, 2018

    Accepted: Nov. 20, 2018

    Published Online: Jul. 30, 2019

    The Author Email: Yanqiong Shi (syq1105@qq.com), Rongsheng Lu (rslu@hfut.edu.cn)

    DOI:10.3788/LOP56.071202

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