Laser & Optoelectronics Progress, Volume. 57, Issue 1, 011204(2020)

Checkerboard Corner Detection Based on Corner Gray Distribution Feature

Ming Wu1,2,3, Junlong Wu1,2,3, Shuai Ma1,2,3, Kangjian Yang1,2, and Ping Yang1,2、*
Author Affiliations
  • 1Key Laboratory of Adaptive Optics, Chinese Academy of Sciences, Chengdu, Sichuan 610209, China
  • 2Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, Sichuan 610209, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    Figures & Tables(11)
    Pixels on circle with radius of 3
    Distributions of pixels on circle in each region. (a) Sum of pixels in any two adjacent regions of circle is half of sum of pixels on circle; (b) pixels at boundary on concentric circle correspond to the same θ
    Distributions of candidate corners before and after iterative refinement. (a) Distribution of candidate corners before iterative refinement; (b) locally enlarged drawing of Fig. 3(a); (c) distribution of candidate corners after iterative refinement; (d) locally enlarged drawing of Fig. 3(c); (e) distribution of candidate corners after eliminating fake corners; (f) locally enlarged drawing of F
    Gradient graphs of candidate corner points
    Flow chart of corner detection
    Contrast experiments of corner detection. (a) Original images; (b) results of corner detection by Matlab Toolbox[15]; (c) results of corner detection by algorithm in Ref. [11]; (d) results of corner detection by proposed algorithm
    Checkerboard with large distortion. (a) Original images; (b) result of corner detection by Matlab Toolbox[15]; (c) result of corner detection by algorithm in Ref. [11]; (d) result of corner detection by proposed algorithm
    10 checkerboard images with different shooting angles
    Re-projection error. (a) Matlab Toolbox[15]; (b) algorithm in Ref. [11]; (c) proposed algorithm (without refinement); (d) proposed algorithm (with refinement)
    • Table 1. Number of corner points detected by different algorithms

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      Table 1. Number of corner points detected by different algorithms

      ImagenumberMatlabToolbox[15]Algorithmin Ref.[11]Proposedalgorithm
      No.1888688
      No.2888888
      No.3888788
    • Table 2. Results of camera calibration

      View table

      Table 2. Results of camera calibration

      Algorithmfxfys /10-2u0 /pixelv0 /pixelk1k2σ /pixel
      Matlab Toolbox[15]2178.821796.82318.87241.87-0.18482.27420.0968
      Algorithm in Ref.[11]2176.22178.20.50313.10244.60-0.15621.34290.0743
      Without refinement2183.62183.20.90313.80246.90-0.1123-1.14000.2412
      With refinement2177.12176.96314.10246-0.14971.03480.0708
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    Ming Wu, Junlong Wu, Shuai Ma, Kangjian Yang, Ping Yang. Checkerboard Corner Detection Based on Corner Gray Distribution Feature[J]. Laser & Optoelectronics Progress, 2020, 57(1): 011204

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Jul. 3, 2019

    Accepted: Jul. 15, 2019

    Published Online: Jan. 3, 2020

    The Author Email: Yang Ping (pingyang2516@163.com)

    DOI:10.3788/LOP57.011204

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