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Haze diffusion path mapping and source determination method based on surveillance video

A technology of diffusion path and monitoring video, applied in image data processing, instrument, character and pattern recognition, etc., can solve the problem of inability to effectively monitor the source of haze in real time and determine the responsible subject.

Active Publication Date: 2017-03-22
BEIJING NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

However, limited by the intricate topographic conditions at a small scale and the scarcity of pollution monitoring equipment, it is impossible to effectively monitor the source of haze in real time and determine the responsible party

Method used

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Embodiment approach

[0019] The invention solves the problem of how to monitor the direct source of the haze in real time. Through the gridded urban area, the monitoring video haze level change analysis and time-varying analysis are used to draw the current haze diffusion path in real time, and then determine the specific haze source grid and determine the source subject. The implementation is as follows:

[0020] 1. Mesh division: According to the geographical location, determine the appropriate size of the grid, and divide the area to be monitored into a grid. Statistically obtain road and video monitoring data in the grid area, and establish an image sample library of all-weather, multi-temporal haze-free benchmark monitoring areas.

[0021] 2. Image haze level recognition: (a) Determine the time interval of image collection, and collect surveillance video images in real time. (b) Remove invalid images, extract image contrast changes, gradient changes, and visibility information, and determin...

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Abstract

The invention discloses a method of adopting a grid to partition a region and analyzing a pollution index change trend reflected by surveillance video data in the grid for tracing the direct haze generation source in real time. The method comprises steps: firstly, grid partitioning is carried out in a region, and a no-haze reference map sample library based on a video image is built for each grid; then, through analyzing the surveillance video image and in combination with the no-haze reference map, based on time sequence analysis, fog and haze are distinguished, and the haze index, the grade, the change trend and the change speed in the surveillance image at the current position are determined; and finally, according to the position of the surveillance video, the haze index, the grade and the trend along with time changes, a haze diffusion path along with time changes is mapped, a grid sequence on the path is further obtained, and finally, a specific pollution source grid and a responsibility subject for the pollution source are determined. The method can be used for timely positioning the direct haze generation source in a specific region, and has the advantages of high recognition precision and high efficiency.

Description

[0001] Technical field: [0002] The invention belongs to the field of computer image processing technology and air pollutant monitoring, and in particular relates to a method for tracing the direct source of haze by analyzing the variation trend of the pollution index reflected by monitoring video data in the grid by adopting grid division. [0003] Background technique: [0004] At present, the sources of atmospheric compound pollution are complex and changing rapidly, and the status quo of air quality improvement is still grim. At present, the policies of "restricting production and stopping production, stopping work and restricting travel" from a macro perspective are non-permanent and temporary "one size fits all" measures, which cannot solve the problems of companies with serious pollution, smuggling emissions, destroying monitoring equipment, and maliciously falsifying monitoring data. The enthusiasm and economic interests of law-abiding enterprises have been greatly dam...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06T7/00G06T7/40
CPCG06T7/0004G06T2207/10032G06T2207/30192G06V20/182G06V20/13
Inventor 余先川詹英田海峰
Owner BEIJING NORMAL UNIVERSITY
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