Road traffic sign detection and classification
- 1 December 1997
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Industrial Electronics
- Vol. 44 (6) , 848-859
- https://doi.org/10.1109/41.649946
Abstract
A vision-based vehicle guidance system for road vehicles can have three main roles: (1) road detection; (2) obstacle detection; and (3) sign recognition. The first two have been studied for many years and with many good results, but traffic sign recognition is a less-studied field. Traffic signs provide drivers with very valuable information about the road, in order to make driving safer and easier. The authors think that traffic signs most play the same role for autonomous vehicles. They are designed to be easily recognized by human drivers mainly because their color and shapes are very different from natural environments. The algorithm described in this paper takes advantage of these features. It has two main parts. The first one, for the detection, uses color thresholding to segment the image and shape analysis to detect the signs. The second one, for the classification, uses a neural network. Some results from natural scenes are shown.Keywords
This publication has 14 references indexed in Scilit:
- Robust road sign detection and recognition from image sequencesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- A real-time traffic sign recognition systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Natural scene segmentation using fractal based autocorrelationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- A Visual Control System Using Image Processing and Fuzzy TheoryPublished by Springer Nature ,1992
- Vision-based Vehicle GuidancePublished by Springer Nature ,1992
- Neural Network Based Autonomous NavigationPublished by Springer Nature ,1990
- Optimal corner detectorComputer Vision, Graphics, and Image Processing, 1989
- Detecting time-varying cornersComputer Vision, Graphics, and Image Processing, 1984
- Gray-level corner detectionPattern Recognition Letters, 1982
- Volumetric model and 3D trajectory of a moving car derived from monocular TV frame sequences of a street sceneComputer Graphics and Image Processing, 1982