Visibility detection in foggy weather based on complex network

Qinyu Zhu; Haicheng Tao; Yanhua Cao

doi:10.1117/12.2622728

1 December 2021 Visibility detection in foggy weather based on complex network

Qinyu Zhu, Haicheng Tao, Yanhua Cao

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 120792D (2021) https://doi.org/10.1117/12.2622728
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

Aiming at the visibility prediction problem that is currently concerned in the transportation and aviation fields, an effective detection method based on complex network theory is proposed. Firstly, preprocess the images in the FROSI data set to obtain the gray image after the background difference subtraction, and derive and calculate the transmittance. Secondly, a corresponding mathematical model based on a complex network is proposed. After three steps of gray contour extraction, recognition parameter extraction, and image recognition and classification, a simulation platform is built and canny operator is used to complete image edge feature contour extraction. Finally, the processed image is combined with the formula to detect the visibility change trend in different time periods and compare it with the true value for comparison, the corresponding evaluation results are obtained from the relative error analysis.

Citation Download Citation

Qinyu Zhu, Haicheng Tao, and Yanhua Cao "Visibility detection in foggy weather based on complex network", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 120792D (1 December 2021); https://doi.org/10.1117/12.2622728

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