Home > Archive>Volume 18, Issue 2, 2022 >103-108. DOI:https://doi.org/10.1007/s11801-022-1024-y
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Estimating the quality of stripe in structured light 3D measurement
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  • XUE Qi

    XUE Qi

    School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China[* This work has been supported by the National Natural Science Foundation of China Nos.61705198 and 61874099, the Certificate of Postdoctoral Research Grant in Henan Province No.001801008, the Henan Innovation Demonstration Project No.201111212300, and the Zhengzhou Major Science and Technology Innovation Project No.2019CXZX0037.
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  • JI Wenzhao

    JI Wenzhao

    School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China[* This work has been supported by the National Natural Science Foundation of China Nos.61705198 and 61874099, the Certificate of Postdoctoral Research Grant in Henan Province No.001801008, the Henan Innovation Demonstration Project No.201111212300, and the Zhengzhou Major Science and Technology Innovation Project No.2019CXZX0037.
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  • MENG Hao

    MENG Hao

    School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China[* This work has been supported by the National Natural Science Foundation of China Nos.61705198 and 61874099, the Certificate of Postdoctoral Research Grant in Henan Province No.001801008, the Henan Innovation Demonstration Project No.201111212300, and the Zhengzhou Major Science and Technology Innovation Project No.2019CXZX0037.
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  • SUN Xiaohong

    SUN Xiaohong

    School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China[* This work has been supported by the National Natural Science Foundation of China Nos.61705198 and 61874099, the Certificate of Postdoctoral Research Grant in Henan Province No.001801008, the Henan Innovation Demonstration Project No.201111212300, and the Zhengzhou Major Science and Technology Innovation Project No.2019CXZX0037.
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  • YE Huiying

    YE Huiying

    School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China[* This work has been supported by the National Natural Science Foundation of China Nos.61705198 and 61874099, the Certificate of Postdoctoral Research Grant in Henan Province No.001801008, the Henan Innovation Demonstration Project No.201111212300, and the Zhengzhou Major Science and Technology Innovation Project No.2019CXZX0037.
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  • YANG Xiaonan

    YANG Xiaonan

    School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China[* This work has been supported by the National Natural Science Foundation of China Nos.61705198 and 61874099, the Certificate of Postdoctoral Research Grant in Henan Province No.001801008, the Henan Innovation Demonstration Project No.201111212300, and the Zhengzhou Major Science and Technology Innovation Project No.2019CXZX0037.
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Affiliation:

School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China[* This work has been supported by the National Natural Science Foundation of China (Nos.61705198 and 61874099), the Certificate of Postdoctoral Research Grant in Henan Province (No.001801008), the Henan Innovation Demonstration Project (No.201111212300), and the Zhengzhou Major Science and Technology Innovation Project (No.2019CXZX0037).

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    Abstract:

    lity of stripe image. In the method, two parameters, skewness coefficient of stripe gray distribution and the noise level, are used to estimate the quality of stripe. The simulation results show that the bigger the skewness coefficient is, the bigger the error of stripe locating results is. Meanwhile, the smaller the noise level is, the smaller the error of stripe locating results is. The method has been used to estimate the experimental image, and the same conclusion can be obtained. The method can be used for recognizing large error data automatically by the two parameters.

    Reference
    [1] HAN J, LIU Y W. Multi-threshold segmentation for center extraction of structured light stripe[J]. Journal of geomatics, 2020, (3)：20-23. (in Chinese)
    [2] LIU X L, HE D, CHEN H L, et al. Techniques of structured light measurement network with 3D sensors[J]. Infrared and laser engineering, 2020, 49(3)：109-118. (in Chinese)
    [3] DING C, TANG L W, CAO L J, et al. Knowledge-based automatic extraction of multi-structured light stripes[J]. Journal of real-time image processing, 2020, 17：1015-1027.
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XUE Qi, JI Wenzhao, MENG Hao, SUN Xiaohong, YE Huiying, YANG Xiaonan. Estimating the quality of stripe in structured light 3D measurement[J]. Optoelectronics Letters,2022,18(2):103-108

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History
  • Received:March 04,2021
  • Revised:August 23,2021
  • Online: February 23,2022
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