Laser & Optoelectronics Progress, Volume. 62, Issue 2, 0215002(2025)

Structured Light Centerline Extraction Method for Ice Surface Based on Normal Guidance

Tao Song1,2、*, Guihua Liu1,2, Huiming Huang1,2, Yunxing Gong1,2, Fuping Qin1,2, and Hao Xie1,2
Author Affiliations
  • 1School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, Sichuan , China
  • 2Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Mianyang 621010, Sichuan , China
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    The accurate extraction of the laser stripe centerline in the three-dimensional measurement system of the icing model is the key to realize the high-precision three-dimensional measurement of the icing model. Aiming at the problem of poor centerline extraction accuracy due to the serious light penetration of the laser stripe on the surface of the ice body, this paper proposes a laser stripe centerline extraction method based on the normal guidance on the surface of the ice body. First, obtain the contour of the laser stripe and the interfering spot and exclude the interfering spot based on the shape of the contour, and at the same time, combine the improved boundary threshold tracking algorithm with the grayscale center of gravity method to coarsely locate the laser centerline. Then, use principal component analysis (PCA) to obtain the normal of the laser centerline obtained from the coarsely located laser centerline. Finally, bi-linear interpolation is performed in the normal direction and combined with the grayscale center of gravity method to obtain the high-precision sub-pixel center point coordinates. The experimental results show that the measurement accuracy of the proposed laser centerline extraction algorithm is 0.035 mm, which is 5.487 times higher than the Steger algorithm, and the extraction speed is 6.578 times higher.

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    Tao Song, Guihua Liu, Huiming Huang, Yunxing Gong, Fuping Qin, Hao Xie. Structured Light Centerline Extraction Method for Ice Surface Based on Normal Guidance[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0215002

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    Paper Information

    Category: Machine Vision

    Received: Mar. 5, 2024

    Accepted: May. 22, 2024

    Published Online: Jan. 3, 2025

    The Author Email:

    DOI:10.3788/LOP240814

    CSTR:32186.14.LOP240814

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