Enhanced fog detection and free-space segmentation for car navigation

Free-space detection is a primary task for car navigation. Unfortunately, classical approaches have difficulties in adverse weather conditions, in particular in daytime fog. In this paper, a solution is proposed thanks to a contrast restoration approach on images grabbed by an in-vehicle camera. The...

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Bibliographic Details
Published in:Machine vision and applications 2014-04, Vol.25 (3), p.667-679
Main Authors: Hautière, Nicolas, Tarel, Jean-Philippe, Halmaoui, Houssam, Brémond, Roland, Aubert, Didier
Format: Article
Language:English
Subjects:
Cameras
Communications Engineering
Computation
Computer Science
Density
Fog
Image acquisition
Image contrast
Image Processing
Image Processing and Computer Vision
Image segmentation
In car entertainment
Navigation
Networks
Object recognition
Pattern Recognition
Restoration
Roads
Segmentation
Special Issue Paper
Vision systems
Weather
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Summary:Free-space detection is a primary task for car navigation. Unfortunately, classical approaches have difficulties in adverse weather conditions, in particular in daytime fog. In this paper, a solution is proposed thanks to a contrast restoration approach on images grabbed by an in-vehicle camera. The proposed method improves the state-of-the-art in several ways. First, the segmentation of the fog region of interest is better segmented thanks to the computation of the shortest routes maps. Second, the fog density as well as the position of the horizon line is jointly computed. Then, the method restores the contrast of the road by only assuming that the road is flat and, at the same time, detects the vertical objects. Finally, a segmentation of the connected component in front of the vehicle gives the free-space area. An experimental validation was carried out to foresee the effectiveness of the method. Different results are shown on sample images extracted from video sequences acquired from an in-vehicle camera. The proposed method is complementary to existing free-space area detection methods relying on color segmentation and stereovision.
ISSN:0932-8092
1432-1769
DOI:10.1007/s00138-011-0383-3