{"title":"用于车辆的雾和无雾场景图像分类","authors":"M. Pavlic, G. Rigoll, Slobodan Ilic","doi":"10.1109/IVS.2013.6629514","DOIUrl":null,"url":null,"abstract":"Today modern vehicles are often equipped with a camera, which captures the scene in front of the vehicle. The recognition of weather conditions with this camera can help to improve many applications as well as establish new ones. In this article we will show how it is possible to distinguish between scenes with clear and foggy weather situations. The proposed method uses only gray-scale images as input signal and is running in real time. Using spectral features and a simple linear classifier, we can achieve high detection rates in both daytime and night-time scenes. Furthermore, we will show that in our application area these features outperform others.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"55","resultStr":"{\"title\":\"Classification of images in fog and fog-free scenes for use in vehicles\",\"authors\":\"M. Pavlic, G. Rigoll, Slobodan Ilic\",\"doi\":\"10.1109/IVS.2013.6629514\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today modern vehicles are often equipped with a camera, which captures the scene in front of the vehicle. The recognition of weather conditions with this camera can help to improve many applications as well as establish new ones. In this article we will show how it is possible to distinguish between scenes with clear and foggy weather situations. The proposed method uses only gray-scale images as input signal and is running in real time. Using spectral features and a simple linear classifier, we can achieve high detection rates in both daytime and night-time scenes. Furthermore, we will show that in our application area these features outperform others.\",\"PeriodicalId\":251198,\"journal\":{\"name\":\"2013 IEEE Intelligent Vehicles Symposium (IV)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"55\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Intelligent Vehicles Symposium (IV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2013.6629514\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Intelligent Vehicles Symposium (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2013.6629514","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of images in fog and fog-free scenes for use in vehicles
Today modern vehicles are often equipped with a camera, which captures the scene in front of the vehicle. The recognition of weather conditions with this camera can help to improve many applications as well as establish new ones. In this article we will show how it is possible to distinguish between scenes with clear and foggy weather situations. The proposed method uses only gray-scale images as input signal and is running in real time. Using spectral features and a simple linear classifier, we can achieve high detection rates in both daytime and night-time scenes. Furthermore, we will show that in our application area these features outperform others.