Latest revision as of 20:54, 3 February 2021

Abstract

Present vision based driver assistance systems are designed to perform under good-natured weather conditions. However, limited visibility caused by heavy rain or fog strongly affects vision systems. To improve machine vision in bad weather situations, a reliable detection system is necessary as a ground base. We present an approach that is able to distinguish between multiple weather situations based on the classification of single monocular color images, without any additional assumptions or prior knowledge. The proposed image descriptor clearly outperforms existing descriptors for that task. Experimental results on real traffic images are characterized by high accuracy, efficiency, and versatility with respect to driver assistance systems.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.5445/ir/1000011965

• https://publikationen.bibliothek.kit.edu/1000011965/895984

• http://xplorestaging.ieee.org/ielx5/4607789/4621124/04621205.pdf?arnumber=4621205,

http://dx.doi.org/10.1109/ivs.2008.4621205

• https://ieeexplore.ieee.org/abstract/document/4621205,

http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000004621205,

https://academic.microsoft.com/#/detail/2154673940

• https://publikationen.bibliothek.kit.edu/1000011965,

https://publikationen.bibliothek.kit.edu/1000011965/895984,

https://doi.org/10.5445/IR/1000011965,

http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:swb:90-119655

DOIS: 10.5445/ir/1000011965 10.1109/ivs.2008.4621205