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
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;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2013 IEEE
Conference_Location :
Gold Coast, QLD
Print_ISBN :
978-1-4673-2754-1
DOI :
10.1109/IVS.2013.6629514