Foggy day detecting method based on image color spatial feature

Abstract

The invention provides a foggy day detecting method based on an image color spatial feature. The method comprises the following steps of first step, obtaining a background picture through a video image or a single image; step 2, performing color space conversion for the background picture, and extracting the color space feature: firstly performing color space conversion for the background picture, converting from an RGB (red-green-blue) color space into an HSV (hue, saturation, value) color space, and extracting the features of various components of the HSV according to the information included image; and step 3, dividing the weather information included image into a non-foggy day, a little foggy day and a dense foggy day according to the identification conditions: at first, if the identification condition 1 is met, the weather is the dense foggy day, otherwise the identification is continued; secondly, if the identification condition 2 is met, the weather is the non-foggy day, otherwise, the identification is continued; and finally, if the identification condition 3 is met, the weather is the little foggy day, otherwise, the weather is the dense foggy day. The method provided by the invention is suitable for being used for monitoring the foggy day in expressways, particularly pre-warning the emergency of agglomerate fog in partial road segments, thus, the safe road driving can be ensured.

Description

technical field [0001] The invention relates to the fields of digital video image processing and traffic weather detection, and is a fog detection method based on image color HSV features. Background technique [0002] Visibility is one of the elements of the road weather condition system. In the traffic high-speed network, the mastery of the visibility of a road is related to the safety of road users' lives and property. The report of vicious traffic accidents caused by low visibility is not uncommon. In the case of low visibility, the reaction speed of human beings is reduced. This is especially true when traveling at high speeds. , Rapid and accurate weather condition information can provide advance warning, thereby helping the highway traffic road management department to manage the highway reasonably and effectively and road users to choose safe road use routes and driving speeds. [0003] At present, the observation of heavy fog is mainly done by manual visual inspec...

AI Technical Summary

Problems solved by technology

Due to the high cost of equipment and the large length of the expressway, it is obviously too expensive to arrange observation stations densely on the expressway to capture the infested fog

[0004] For the image-based traditional fog visibility detection technology, the camera needs to be calibrated on-site, which not only needs to know the internal parameters of the camera, but also needs to know the installation position and angle, and needs to correspond to the corresponding scene. The calculation is complex and The cost is also relatively high

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