A Transmission Line Icing Detection Method based on Improved Canny and Hough Transform

Authors

  • Shilong Liu

DOI:

https://doi.org/10.54691/hw55ts77

Keywords:

Detection of Ice Coating on Transmission Lines, Improved Canny Operator, Adaptive Double Threshold, Optimized Hough Transform, Camera Imaging Principle.

Abstract

To address the issues of noise interference in edge detection of transmission line icing images and inaccurate thickness calculation due to scattered straight line detection, a detection method based on an improved Canny operator and optimized Hough transform is proposed. The Canny adaptive double threshold is achieved through the percentile sorting of gradient magnitude to enhance the robustness of edge extraction; the optimized Hough transform with line fitting is adopted to fuse scattered edges into complete icing edge lines ; and the thickness conversion is completed in combination with the camera imaging principle. Experiments show that this method can effectively improve the accuracy of icing thickness detection and has engineering application value.

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References

[1] L. Zhang, Q. Liu and H. Sun: Image-Based Monitoring Method for Transmission Line Icing Under Complex Backgrounds, Sensors, Vol.22 (2022) No.15, p.5824.

[2] M. Hu, J. He and M. Alsabaan: Image Identification Method of Ice Thickness on Transmission Line Based on Visual Sensing, Mobile Networks and Applications, Vol.28 (2023) No.5, p.1783-1792.

[3] Y. Yang, S. Hua, H. Wang, M. Li, Q. He, M. Zhao and Y. Wan: Detection Method of Icing Thickness of Overhead Transmission Lines Based on Canny Algorithm, International Journal of Energy Technology and Policy, Vol.19 (2024) No.3, p.344-362.

[4] W. Song, P. Li and M. Wang: Transmission Line Detection Based on Improved Hough Transform, Journal of Physics: Conference Series, Vol.2488 (2023) No.1, p.012045.

[5] X. Li, Y. Chen and Z. Zhao: Vision-Based Ice Thickness Measurement Method for Transmission Lines Using Edge Detection and Geometric Calibration, IEEE Access, Vol.10 (2022), p.118742-118751.

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Published

24-03-2026

Issue

Section

Articles