Underground cable laying environment survey method based on wide-angle image distortion removal algorithm

Xiaomin Huang; Jiayun Gao; Xipeng Zhang

doi:10.1117/12.3029747

21 June 2024 Underground cable laying environment survey method based on wide-angle image distortion removal algorithm

Xiaomin Huang, Jiayun Gao, Xipeng Zhang

Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 1316718 (2024) https://doi.org/10.1117/12.3029747
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China

Abstract

Study the method of underground cable laying environment survey based on wide-angle image distortion removal algorithm, understand the underground cable laying situation, and improve the security of power grid. After correcting the distortion of the wide-angle depth image of the downhole cable laying environment through the nonlinear model method, the cable nameplate coordinates are located, and the raspberry Pie carries its own high-definition camera to shoot the cable nameplate, Obtain the environmental information of cable laying space and cable nameplate, and collect and display the environmental information of temperature, humidity and gas concentration in the cable well using temperature, humidity and gas sensors. The experimental results show that this method can effectively survey the underground cable laying environment, not only can accurately capture the spatial environment information of underground cable laying, accurately identify the environmental information contained in the cable nameplate, but also can simultaneously detect the temperature, humidity and various gas concentrations in the power well, which has a good application effect.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaomin Huang, Jiayun Gao, and Xipeng Zhang "Underground cable laying environment survey method based on wide-angle image distortion removal algorithm", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 1316718 (21 June 2024); https://doi.org/10.1117/12.3029747

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KEYWORDS

Distortion

Environmental sensing

Image segmentation

Cameras

Image processing

Optical character recognition

Image sensors

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