Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1815014(2022)

Improved Calibration Method of Camera Internal Parameters Based on Nonlinear Optimization

Yidong Liu and Zhentang Jia*
Author Affiliations
  • College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China
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    Figures & Tables(14)
    Main flow of camera calibration
    Coordinate transformation of camera imaging
    Improved calibration process of camera
    Calibration images at different positions
    Calibration image after corner extraction
    Optimization results of two PSO algorithms
    Position relationship between actual corner and reprojection corner
    Reprojection error of different calibration methods. (a) Calibration toolbox; (b) Zhang calibration method; (c) proposed method
    Search performance comparison of four intelligent optimization algorithms
    • Table 1. Linear solution of camera internal parameters

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      Table 1. Linear solution of camera internal parameters

      Parameterfxfyu0v0k1k2 k3p1p2
      Value10214.3310214.33643.25482.5200
    • Table 2. Results of PSO with different iterations

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      Table 2. Results of PSO with different iterations

      ParameterNumber of iterations
      100200300400
      fx10208.0410209.0910207.7810208.23
      fy10205.381.02053810204.8910204.25
      u0644.51644.46645.0140644.72
      v0482.76482.22486.280481.77
      k1-7.72-5.4735-4.1863-3.3107
      k20.1996-2.0780-0.43040.2064
      k3-5.2160-4.9430-4.6964-4.5130
      p1-0.0862-0.0254-0.02610.0006
      p20.11970.08210.06430.0632
      Fitness0.42000.38520.35340.3195
    • Table 3. Results of DWAMPSO with different iterations

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      Table 3. Results of DWAMPSO with different iterations

      ParameterNumber of iterations
      100200300400
      fx10214.3510214.3110214.3110218.25
      fy10219.2910216.5010216.3410217.61
      u0645.5413645.4992645.5005645.4854
      v0481.3720481.4797481.4860481.4947
      k1-0.1778-0.1897-0.1681-0.3372
      k2-4.4974-4.4636-4.4629-4.3837
      k3-8.0918-7.3946-7.5034-9.3731
      p10.00420.00110.00100.00002
      p20.00050..00220.00170.0017
      Fitness0.04600.03720.03700.0368
    • Table 4. Fitness results of different algorithms

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      Table 4. Fitness results of different algorithms

      AlgorithmOptimal fitnessWorst fitness
      DE0.21520.3033
      GA0.15720.2389
      PSO0.31950.4075
      DWAMPSO0.03680.1694
    • Table 5. Convergence rate of different algorithms

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      Table 5. Convergence rate of different algorithms

      AlgorithmFitness10.80.60.40.2
      GDIteration number3643109186
      Running time /s38.905746.1268117.1337197.2784
      DEIteration number184202246278
      Running time /s156.2791171.8147210.1576239.0557
      GAIteration number43125169268351
      Running time /s44.7721129.5620176.4058280.4783368.7568
      PSOIteration number478287147
      Running time /s40.978773.157477.9820142.2541
      DWAMPSOIteration number1212134154
      Running time /s11.628911.628912.538138.088150.2417
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    Yidong Liu, Zhentang Jia. Improved Calibration Method of Camera Internal Parameters Based on Nonlinear Optimization[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1815014

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    Paper Information

    Category: Machine Vision

    Received: Jun. 7, 2021

    Accepted: Aug. 25, 2021

    Published Online: Aug. 22, 2022

    The Author Email: Jia Zhentang (462458081@qq.com)

    DOI:10.3788/LOP202259.1815014

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