Image grey level histogram-based foggy day detection method

A grayscale histogram and image grayscale technology, applied in the field of image processing and traffic video detection, can solve the problem of difficult fog detection, and achieve the effect of good detection effect, high accuracy and fast running speed.

Inactive Publication Date: 2010-09-01
SOUTHEAST UNIV
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Problems solved by technology

[0009] The present invention is a fog detection method based on image grayscale histogram. For the first time, the grayscale histogram of the image is used for fog detection, and three weather grade

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  • Image grey level histogram-based foggy day detection method
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  • Image grey level histogram-based foggy day detection method

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[0045] specific implementation plan

[0046] The present invention is a kind of fog detection method based on image gray level histogram, concrete steps are as follows:

[0047]Step 1, initialization, read in road traffic images or videos, obtain image information, use image processing technology, uniformly convert it into a grayscale image, and calculate the total number of image pixels num, and then obtain the grayscale histogram of the image. For example, the specific steps in matlab are, [m, n, r]=size(f); if(r==1)g=f; elseg=rgb2gray(f); end; num=m*n; hist=imhist (g); where f is the read-in image, g is the grayscale image converted from the original image, num is the total number of image pixels obtained, and hist represents the grayscale histogram of the image, that is, the grayscale value of the image The corresponding relationship with the number of pixels;

[0048] Step 2. According to the corresponding relationship between each gray level and the number of pixels in...

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Abstract

The invention discloses an image grey level histogram-based foggy day detection method, which mainly comprises: a first step of performing initialization to obtain a grey level histogram of an image; a second step of primarily detecting whether the image is marked to indicate a foggy day or a fogless day; a third step of performing processing again if the image is marked to indicate the fogless day, and marking the image to indicate the foggy day when a certain condition is met; a fourth step of further performing detection if the image is marked to indicate the foggy day, and marking the image to indicate the fogless day when the certain condition is met; and a fifth step of performing the detection for the third time if the image is marked to indicate the foggy day, marking the image to indicate a densely-foggy day when the certain condition is met, otherwise, marking the image to indicate a thinly-foggy day. In the method, the grey level histogram of the image is utilized to detect weather for the first time, and three levels which are the fogless day, the thinly-foggy day and the densely-foggy day respectively are detected by utilizing corresponding relationships between the number of pixels and grey level values in the grey level histogram and a series of threshold values. Compared with other foggy day detection methods, the method has the advantages of low cost, easy popularization, high processing speed, wide application range, high accuracy and ideal effect.

Description

technical field [0001] The invention relates to the field of image processing and traffic video detection, is a fog detection method based on image gray histogram, and is mainly applied to fog detection in urban traffic or expressways. Background technique [0002] In modern society, the importance of road traffic is self-evident, and in the field of traffic, it can be said that heavy fog with low visibility, especially the phenomenon of "fog" that exists or suddenly occurs in some areas, is the cause of large-scale traffic such as "rear-end collision". The culprit of the accident. At present, the technology of fog detection is very lacking. In many cases, only when a traffic accident occurs, the relevant road section will be found to have heavy fog. [0003] The current methods for detecting foggy days are mainly as follows: [0004] Under certain seasonal weather conditions, use manpower and vehicles to patrol; [0005] The monitoring station is specially installed, mai...

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Application Information

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IPC IPC(8): G01W1/00
Inventor 路小波刘阳
Owner SOUTHEAST UNIV
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