An improved internal advancement algorithm for light stripe center extraction

Xu Li; Ji Ya

doi:10.11884/HPLPB202537.240346

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Article Navigation > High Power Laser and Particle Beams > 2025 > Accepted Manuscript

Xu Li, Ji Ya. An improved internal advancement algorithm for light stripe center extraction[J]. High Power Laser and Particle Beams. doi: 10.11884/HPLPB202537.240346

Citation:

Xu Li, Ji Ya. An improved internal advancement algorithm for light stripe center extraction[J]. High Power Laser and Particle Beams. doi: 10.11884/HPLPB202537.240346

Xu Li, Ji Ya. An improved internal advancement algorithm for light stripe center extraction[J]. High Power Laser and Particle Beams. doi: 10.11884/HPLPB202537.240346

Citation:

Xu Li, Ji Ya. An improved internal advancement algorithm for light stripe center extraction[J]. High Power Laser and Particle Beams. doi: 10.11884/HPLPB202537.240346

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An improved internal advancement algorithm for light stripe center extraction

doi: 10.11884/HPLPB202537.240346

Xu Li^,,
Ji Ya

School of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China

Received Date: 2024-09-28
Accepted Date: 2025-02-12
Rev Recd Date: 2025-02-20

Available Online: 2025-04-08

Abstract

Abstract

Aiming at the problems of low extraction accuracy and weak anti-interference ability of line structure light centroids in turbid water bodies, this study proposes an improved internal advancement algorithm, which aims to enhance the accuracy and robustness of the extraction of line structure light centroids in complex environments. Firstly, the median filter is used to preprocess the image to suppress the noise, and combined with the eight-neighborhood method to quickly locate the starting point of the light stripe; subsequently, the grayscale neighborhood attribute method is introduced to dynamically estimate the pixel width of the current line of the line structured light, and based on the range of the maximum interclass variance method is applied to adaptively determine the binarized threshold value, which effectively reduces the background interference; finally, the grayscale gravity method is used to calculate the initial centroid in the constrained range of pixel widths and use this as the basis to advance upward and downward to search for the center point of the line structured light. Comparison tests are conducted in various turbid water environments and different structured light patterns. The results show that compared with the original internal advancement algorithm, the root mean square error of this paper's method is reduced by 13.33%, and the running speed of the algorithm is increased by 69.07% compared with Steger's algorithm, which realizes the balance between accuracy and speed.
- structured light,
- center point extraction,
- self-adaption,
- pixel width

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References(19)

References

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