Numerical analysis of local dense fog by video image
monitoring of luminous objects

Abstract

Abstract: The video image monitoring technology of highway horizontal visibility is developing rapidly, and has become one of the important means of local dense fog weather monitoring and early warning. In order to prevent road fog traffic accidents effectively, referring to the definition of local dense fog and the regulation of early warning level, this paper statistically analyzes the luminance parameters of luminous objects at fixed road distance in different visibility environments of dense fog and non-dense fog based on the video and visibility data of road fog-prone sections, and explores the correlation between the luminance value of luminous objects and the horizontal visibility value at different distances in dense fog section. Then, based on the correlation analysis between the luminance parameter changes and the horizontal visibility of the video feature image, a method to estimate the horizontal visibility using the numerical analysis results is presented, which provides a new idea and realization way for the establishment of local dense fog weather early warning. The results show that: (1) It is scientific, innovative and feasible to monitor the visibility through monitoring the luminance change in different areas of the video image, which can realize 24 h continuous monitoring and early warning. (2) By introducing the contrast analysis of the luminance of the luminous object and that of the environment, the problem that the luminance of the image varies greatly at different time of the day can be overcome. (3) The monitoring of local dense fog can be realized by monitoring the luminous objects at a fixed distance, which can solve the problem that the horizontal scale of local dense fog is difficult to be directly monitored by instruments. (4) The monitoring results of the luminous target video monitoring method can be combined with the internet, geographic information system and navigation information system, so as to realize the purpose of issuing early warning quickly and accurately, and reducing traffic accidents.

Key words: luminous objects, local dense fog section, video images, numerical analysis

CLC Number:

TP391
U495

LU Zhenli , YANG Chengfang , ZHENG Zongjie , CUI Guangshu , AN Yuan . Numerical analysis of local dense fog by video image monitoring of luminous objects[J]. Journal of Atmospheric and Environmental Optics, 2023, 18(2): 119-132.

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Numerical analysis of local dense fog by video image monitoring of luminous objects

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