Long-Range Road Detection for Off-line Scene Analysis
Abstract
Long-range detection of road surface in a sequence of images from a front camera aboard a vehicle is known as an unsolved problem. We propose an
algorithm using a single camera and based on color segmentation which has interesting performance and which is stable along the sequence whatever its length. It is an off-line algorithm which makes good use of current and successive images to build reliable models of the color aspects of the road and of its environment at each vehicle position. To apply the proposed algorithm a radiometric calibration step is required to ensure uniform responses of the pixels over the image. The algorithm consists in three steps: image smoothing consistent with perspective effect on the road, building of the models of the road and non-road colors, and region growing of the road region. The relevance of the proposed algorithm is illustrated by an application to the roadway visibility estimation in stereovision and its performance are illustrated by experiments in difficult situations.
Reference
@inproceedings{jpt-iv09,
author = {Tarel, Jean-Philippe and Bigorgne, Erwan},
title = {Long-Range Road Detection for Off-line Scene Analysis},
booktitle = {Proceedings of IEEE Intelligent Vehicle Symposium (IV'2009)},
date = {June 3-5},
address = {Xian, China},
year = {2009},
pages = {15-20},
note = {http://perso.lcpc.fr/tarel.jean-philippe/publis/iv09.html}
}
Pdf file (3122 Kb)
(c) IEEE