the road sign recognition groups in the world

Contents :
Brief history excursion
A list of reasearch groups and activities
Publications and references related to the road sign recognition
Basic documents

Brief history excursion

The first works related to the road sign recognition have been published (as far as I know) in Japan in 1984. The aim was to try various computer vision methods for the detection of the objects in outdoor scenes. At the begining of nineties, several groups interested in the subject emerged. We may found there solutions focused on particular road sign type together with more general systems. There were reported various approaches for the sign detection (employing of edges, colour segmentation, correlation etc.) in these works. The classification step has been - in most cases - solved by the use of neural network. I find the compilation of Lalonde and Li from CRIM (Canada) the most valuable information source describing systems before 1995.

Presently, there exist several groups, involved in the road sign recognition, in the world. Undoubtly, the most advanced system is the German TSR (Traffic Sign Recognition System) developed at the University Koblenz-Landau in cooperation with Daimler-Benz.

A list of reasearch groups and activities

Universita di Parma Department of Informatics
Bertozzi, Broggi, Fascioli
  • ARGO - semi-autonomous car based on Linux. Several vision algorithms
Koblenz-Landau Univ. Image recognition lab.
Priese, Lakmann, Rehrmann, Lutz, Klieber, Jens
  • robust road sign recog. system, modular conception, NN class.
  • 1994 real time, autonomous vehicle, road tracking, obstacle detection, lane analysis, real time road signs recognition
Research Center Ulm, Daimler Benz AG Ritter, Bartneck, Zheng, Yong-Jian, Werner, Janssen, Reinhard
  • 1990 colour sequences, high order NNet, hypotheses, regions in the image
  • 1992 colour segmentation, polynomial classifiers
  • 1994 VITA II vehicle (hybrid parallel PowerPC), k-NN class., Radial Basis Function network (RBF) (for onchip implementation)
Texas A&M Univ Dept. of Electr. Eng., College Station,TX, USA
Kehtarnavaz, Estevez, Griswold, Kang
  • 1994 feature extraction from occluded images based on colours, NNet
  • 1996 TMS320C40, RGB segmentation, stop and yield signs, HSV segment., Sobel, Hough transform., morphology, boundary countour
Genoa Univ. Italy Dipartimento do Fisica
Piccoli, de Micheli, Parodia, Campani, Nicchiotti, Ottaviani, Castello
  • gray level and colour (if possible), edges, cross-correlation with candidate region, Kalman filtering.
  • classification of scene objects (cars, signs, buildings...)
  • shape based and colour based approaches
  • optical processing (spatial light modulators)
Inst.fur Algoritmen und Kognitive Syst. Karlsruhe Frank, Haag, Kollnig
  • 3D model for occluding scene situations
US Army Env. Fort Meade Kellmayer, Zwahlen
  • driver assistence or highway signs inventory system, BP NNet, fixed colour segmentation, warning signs
Dept.of Transport. Mng. Taipei, Taiwan Fann Jeun-Haii, Lee Gang
  • colour based signs finder for highways
Osaka Nat.Research Inst. Matsuoka, Taniguchi, Mokuno
  • Opticall correlations for road signs detection
ENST de Bretagne, Brest Guibert, Attia
  • Optical correlator for road signs recognition, PSA Peugeot Citroen
GRPR, Ecole Polytechnique, Brest Cohen, Herve, Tong, Gouailler, Fourt, Lina.

Publications and references related to the road sign recognition

Abstracts of the road sign recognition articles from the INSPEC database (text files) : 1, 2, 3, 4, 5,

Basic documents

  1. Nagel H.H. - Computer Vision for Support of Road Vehicle Drivers (local HTML)
    Basic ideas about the Driver Support System - an on-board vehicle device providing a valuable information source to the human driver. The computer vision plays the crucial role in the construction of such system. The aim is to percieve and interpret the traffic scene in order to offer solutions of dangerous situations in heavy traffic.
  2. Lalonde, Li - Road Signs Recognition - Survey of the State of the Art (zipped PostScript, 56kB)
    The compilation of results up to 1995, the brief description of methods, problems and solutions. The valuable source that brings you into the field.

If you are interested in the topic or miss something on this page, contact Pavel Paclik.
Last modified: Sun May 16 09:51:26 CEST 1999