DocumentCode :
3502035
Title :
Classification of images in fog and fog-free scenes for use in vehicles
Author :
Pavlic, Mario ; Rigoll, Gerhard ; Ilic, Slobodan
Author_Institution :
Traffic Technol. & Traffic Manage., BMW Group, Munich, Germany
fYear :
2013
fDate :
23-26 June 2013
Firstpage :
481
Lastpage :
486
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.
Keywords :
fog; image classification; meteorology; natural scenes; road vehicles; spectral analysis; traffic engineering computing; clear weather situations; daytime scenes; detection rates; fog scene capturing; fog-free scene capturing; foggy weather situations; gray-scale images; image classification; input signal; linear classifier; night-time scenes; spectral features; weather condition recognition; Cameras; Feature extraction; Histograms; Meteorology; Roads; Vectors; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2013 IEEE
Conference_Location :
Gold Coast, QLD
ISSN :
1931-0587
Print_ISBN :
978-1-4673-2754-1
Type :
conf
DOI :
10.1109/IVS.2013.6629514
Filename :
6629514
Link To Document :
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