Acta Optica Sinica, Volume. 44, Issue 2, 0212004(2024)

Surface Grid Calibration of Line Structured Light Based on Ray-Tracing

Xiaoqian Wang1, Kun Xu2, Shoucang Wu2, Tao Peng1, Zhenzhen Huang1, and Zhijiang Zhang1、*
Author Affiliations
  • 1Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication & Information Engineering, Shanghai University, Shanghai 200444, China
  • 2MCC Baosteel Technology Service Co. Ltd., Shanghai 201999, China
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    Figures & Tables(20)
    Line structured light vision system
    Schematic diagram of horizontal ray-tracing. (a) Curved light surface; (b) camera ray plane
    Line structured light imaging geometry model
    Schematic diagram of line structured light surface grid
    Intersecting grid points
    Subpixel light strip center point
    Calibration system flow chart
    Field of line structured light surface calibration experiment
    Polynomial fitting results. (a) Horizontal ray-tracing; (b) vertical ray-tracing
    Local results of the ray-tracing grid
    Calibration plane reconstruction with error distribution. (a1) (a2) Proposed method; (b1) (b2) LPM; (c1) (c2) PFC
    Results of distance measurement
    • Table 1. Camera calibration parameters

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      Table 1. Camera calibration parameters

      Parameter nameResult
      fxfy3479.8270,3480.1814
      u0v02536.5745,2621.4617
      k1k2k3-0.07170,0.08888,-0.02706
      p1p20.00114,0.00015
    • Table 2. Polynomial fitting results of different orders

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      Table 2. Polynomial fitting results of different orders

      MethodOrder of polynomial
      23456
      RMSE S /mmHorizontal ray-tracing8.6471.8411.20810.75430.661
      Vertical ray-tracing3.3040.5850.3950.3840.527
      Time T /sHorizontal ray-tracing1.3651.2821.2821.2871.218
      Vertical ray-tracing0.3430.2830.3150.3000.276
      Number of polynomials NPHorizontal ray-tracing20051955192418991861
      Vertical ray-tracing562506495481459
    • Table 3. Calibration results with different number of calibration images

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      Table 3. Calibration results with different number of calibration images

      MethodNumber of calibration images
      4030201510
      Mean error E /mmHRT0.7640.6700.5870.6700.582
      VRT0.2910.2900.2280.2660.347
      Proposed method0.6780.6010.5240.5920.548
      Number of sample points NSHRT437483193220061103664350
      VRT9725710543282490739
      Proposed method534733903724389128565089
      Number of polynomials NPHRT1924187616211043558
      VRT495466402265100
      Proposed method2419234220231308658
    • Table 4. Calibration accuracies of Gaussian noise with different mean values

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      Table 4. Calibration accuracies of Gaussian noise with different mean values

      MethodWithout noiseMean value of Gaussian noise μG
      246810
      HRT0.7640.7330.7490.7320.7320.747
      VRT0.2910.2650.2850.2650.2630.284
      Proposed method0.6780.6480.6640.6460.6460.662
      LPM0.1260.1250.1270.1250.1250.127
      PFC38.27538.71038.27738.71438.71238.279
    • Table 5. Calibration accuracies of Gaussian noise with different standard deviations

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      Table 5. Calibration accuracies of Gaussian noise with different standard deviations

      MethodWithout noiseStandard deviation of Gaussian noise σG
      5101520
      HRT0.7640.7320.7330.7320.747
      VRT0.2910.2640.2640.2630.284
      Proposed method0.6780.6460.6470.6460.662
      LPM0.1260.1250.1250.1250.127
      PFC38.27538.71138.71538.71438.279
    • Table 6. Accuracies of plate measurement

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      Table 6. Accuracies of plate measurement

      Distance

      DP /mm

      MethodNumber of calibration images
      40 planer targets30 planer targets20 planer targets15 planer targets10 planer targets
      1294.47Proposed method0.5200.5180.5230.638
      LPM0.5710.6300.6240.544
      PFC3.7689.86320.81550.740
      1589.78Proposed method0.8350.8320.8970.9870.820
      LPM0.8890.9241.0451.2861.266
      PFC34.38227.74435.07422.60825.357
      1693.48Proposed method0.9960.9930.9991.0230.979
      LPM1.1341.1401.2031.6301.596
      PFC18.5896.76412.29616.51215.035
      1767.24Proposed method0.9591.0791.0651.1481.016
      LPM1.1341.0851.1211.5431.362
      PFC6.3317.9734.4419.2637.340
    • Table 7. Accuracies of distance measurement

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      Table 7. Accuracies of distance measurement

      MethodDistance to be measured
      d1 /mmd2 /mmd3 /mmd4 /mmdH /mmdV /mm
      HRT0.0171.1390.1770.7440.0300.046
      VRT0.8060.0260.4710.0640.0240.034
      Proposed method0.3990.2800.3400.3540.0280.030
      LPM0.1131.0590.1510.6040.0270.038
      PFC3.5758.5016.9521.0010.4930.202
    • Table 8. Measurement accuracies of standard body size unit: mm

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      Table 8. Measurement accuracies of standard body size unit: mm

      MethodHRTVRTProposed methodLPMPFC
      Length0.4790.1450.0250.4576.643
      Width0.3270.4800.0620.1871.386
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    Xiaoqian Wang, Kun Xu, Shoucang Wu, Tao Peng, Zhenzhen Huang, Zhijiang Zhang. Surface Grid Calibration of Line Structured Light Based on Ray-Tracing[J]. Acta Optica Sinica, 2024, 44(2): 0212004

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Sep. 11, 2023

    Accepted: Nov. 1, 2023

    Published Online: Jan. 11, 2024

    The Author Email: Zhang Zhijiang (zjzhang@staff.shu.edu.cn)

    DOI:10.3788/AOS231544

    CSTR:32393.14.AOS231544

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