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A visibility measurement method based on machine learning

A technology of machine learning and measurement method, which is applied in the field of image processing, can solve the problems of low recognition accuracy and achieve the effects of high recognition accuracy, easy installation and simple method

Pending Publication Date: 2019-05-10
南京蓝绿物联科技有限公司
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Problems solved by technology

[0005] The purpose of the present invention is to provide a method for measuring visibility based on machine learning, which solves the problem of low recognition accuracy of the four levels of good air quality, light pollution, moderate pollution, and heavy pollution in the traditional ROI method of extracting images technical issues

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  • A visibility measurement method based on machine learning
  • A visibility measurement method based on machine learning
  • A visibility measurement method based on machine learning

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Embodiment Construction

[0032] Such as Figure 1-Figure 9 Shown is a method for measuring visibility based on machine learning, comprising the following steps:

[0033] Step 1: collect the sample image by the image capture device, and the image capture device sends the sample image to the central server for processing;

[0034] Step 2: The central server extracts the ROI image of the sample image through the ROI extraction method based on the salient area;

[0035] Such as image 3 As shown, the present invention selects a pane of interest on the sample image, and extracts the ROI image from the image in the pane of interest.

[0036] Step 3: The central server preprocesses the sample image, sets a target area in the sample image as the detection area, fills the small concave part of the sample image, eliminates small particle noise in the target area and enhances contrast linearly broadens and enhances edge information features;

[0037] Such as Figure 4 to Figure 7 As shown, when the sample im...

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Abstract

The invention discloses a visibility measurement method based on machine learning and belongs to image processing technology field, The method comrpiseses extracting ROI images, reprocessing images, establishing a binary tree-based multi-classification support vector machine model; processing the sample image. The technical problem that the recognition accuracy of four grades of good air quality,light piollution, medium pollution and heavy pollution is low since traditional method for extracting the ROI of the image is adopted is solved, a salient image obtained based on an image frequency domain is utilized, an interest pane extracted according to a salient region in the extraction process has representativeness in a picture, the characteristics of the image can be fully reflected, and the characteristic value extracted from the interest pane has high distinction; for images with low visibility, edge information characteristics need to be enhanced to improve the matching accuracy, the method adopts contrast linear broadening to enhance the edge information characteristics, and the method is simple and convenient to install, low in price, high in sensitivity and simple and convenient to operate.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a method for measuring visibility based on machine learning. Background technique [0002] Atmospheric visibility has a great impact on people's safe travel in life. Traffic accidents caused by low road visibility levels caused by severe weather such as smog and sand dust occur from time to time, and the existence of fog on expressways has also greatly increased. Uncertainty about people's travel safety. Therefore, timely detection of road visibility levels is of great significance to traffic safety, and many scholars at home and abroad are also conducting in-depth research on this. Instrument measurement and visual measurement are currently two commonly used methods for measuring visibility levels. Among them, the instrument measurement method of visibility level using the transmission method or scattering method in the optical principle is more widely used, but these ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/00G06K9/62G06T5/30
Inventor 邹修国邱新法郑乃山张世凯姚和阳吴佳鸿
Owner 南京蓝绿物联科技有限公司
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