Authors:
Philippe Foucher
;
Pierre Charbonnier
and
Houssem Kebbous
Affiliation:
Laboratoire des Ponts et Chaussées, France
Keyword(s):
Image analysis, Road sign detection, Road sign inventory, Color, Shape, Symmetry, Evaluation.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Implementation of Image and Video Processing Systems
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
In this paper, we introduce a pre-detection algorithm dedicated to French danger-warning and prohibitory road signs. The proposed method combines color, shape, location and symmetry features to select among large image databases, a small subset of pictures that probably contain road signs. We report the results of a systematic experimental assessment that we performed on five image databases, comprised of more than 26,000 images, covering 176 km and containing 371 traffic signs, among which a non-negligible amount (about 5% in average) is damaged. The experiments show that about 10% images of the sequences are selected and more than 87% traffic signs are detected. The missed objects always correspond to dirty, worn-out or badly oriented signs that would be difficult to detect even for a human operator.