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Fuzzy Membership Grade-Based Binocular Line-Structured Light Parameter Calibration Algorithm

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Abstract

This paper presents a binocular stereo calibration algorithm using linear-structured light under high-precision industrial measurement situations. We propose a kind of light plane calibration method that improves accuracy using line-structured light and stereo vision. It has more matching points and higher location accuracy. Firstly, we extract the laser points from stereo image pairs accurately with the designed target after intrinsic parameters calibrated by the Tsai method. Secondly, we match the laser points and reconstruct them in 3d space to obtain the 3d laser point. Repeat the point obtain process in different positions until the 3d laser point set consists of enough points. Then, we construct an optimization problem with fuzzy membership grades expert weight. Finally, the light plane is calibrated by solving the optimization problem with the least square method. The algorithm’s availability is assessed by applying a self-referenced line-structured light scanning system with two cameras. Experimental results indicate that the RMS calibration error with the proposed algorithm is less than 0.033 mm, and the scanning error is 0.064 mm.

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Acknowledgements

This work is financially supported by the National Natural Science Foundation of China (NO. 52175378) and the Fundamental Research Funds for the Central Universities (NO. 3132022215).

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Authors and Affiliations

  1. Marine Engineering College, Dalian Maritime University, Dalian, 116026, China

    Yi Wei, Kuo Wang & Benzhuang Yue

Authors
  1. Yi Wei
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  2. Kuo Wang
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  3. Benzhuang Yue
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Correspondence to Yi Wei.

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Wei, Y., Wang, K. & Yue, B. Fuzzy Membership Grade-Based Binocular Line-Structured Light Parameter Calibration Algorithm. Int. J. Fuzzy Syst. 25, 347–357 (2023). https://doi.org/10.1007/s40815-022-01389-7

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  • DOI: https://doi.org/10.1007/s40815-022-01389-7

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