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高速公路雾图像能见度的监测与识别方法研究

韩格格 李香芳 蒋伊泽

气象研究与应用2024,Vol.45Issue(2):50-56,7.
气象研究与应用2024,Vol.45Issue(2):50-56,7.DOI:10.19849/j.cnki.CN45-1356/P.2024.2.08

高速公路雾图像能见度的监测与识别方法研究

Research on monitoring and recognition technology of highway fog image visibility

韩格格 1李香芳 2蒋伊泽3

作者信息

  • 1. 中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室,银川 750002||宁夏回族自治区气象信息中心,银川 750002
  • 2. 中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室,银川 750002||宁夏回族自治区气象服务中心,银川 750002
  • 3. 中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室,银川 750002||盐池县气象局,宁夏 盐池 751599
  • 折叠

摘要

Abstract

In recent years,automatic visibility stations have been set up along expressways to monitor fog,which has played an important role in ensuring traffic safety.However,the automatic visibility stations are generally far away from each other,and cannot monitor local fogs and mass fogs in a small range.Therefore,this paper proposes a visibility recognition method based on fog images on expressways.The collected highway fog weather images are preprocessed,and the image features,monitoring factors and interest panes with high correlation with visibility are selected.Machine learning method is also adopted to explore the relationship between image features and visibility in fog weather,a binary linear regression model for visibility in fog weather is constructed,and the output results of the monitoring model is verified.The results show that:(1)through the experiment,it is proved that the mean value of saturation and the variance of chroma have a high correlation with visibility,while the three color features of red,green and blue have a low correlation with visibility,indicating that saturation and chroma are the key factors for visibility monitoring,rather than color.(2)By dividing different visibility levels,the image visibility is determined based on the random forest algorithm,and the classification accuracy of the model reaches 90%,which has a strong classification ability for the determination of the visibility interval of the images.(3)The binary linear regression model with different visibility levels is constructed,and the verification results of the verification data set show that the visibility prediction accuracy of the model is high,and the predicted values are all within the correct range,of which 70%of the predicted values were very close to the true values.

关键词

/图像识别/高速公路/监测模型/能见度

Key words

fog/image recognition/highway/monitoring model/visibility

分类

大气科学

引用本文复制引用

韩格格,李香芳,蒋伊泽..高速公路雾图像能见度的监测与识别方法研究[J].气象研究与应用,2024,45(2):50-56,7.

基金项目

中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室开放研究项目(CAMF-202206) (CAMF-202206)

气象研究与应用

1673-8411

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