Road Sign Recognition: A Study of Vision-based Decision Making for Road Environment Recognition

  • Marie de Saint Blancard
Part of the Springer Series in Perception Engineering book series (SSPERCEPTION)


This study is based on an application of vertical road sign recognition by vision. Three types of danger warning signs are recognized. Octagonal stop signs and triangular danger warning signs are distinguished from round forbidding signs on the basis of their outside shape. This recognition is made in “quasi-real-time” in a running vehicle. In addition to the vision algorithm strategy developed, three decision-making softwares are compared: structured programming, expert system approach, and a neural network.


Stop Sign Closed Contour Road Sign Vision Algorithm Manufacture Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Akatsuka, H., and Imai, S. (1988). “Road Signposts Recognition System.” 0096–736 X 88/19601–0936 $02.30, copyright 1988, Society of Automotive Engineers, Inc.Google Scholar
  2. [2]
    EIA (1990). “GIPS Vision.” Manufacturer’s manual, Bièvres, France.Google Scholar
  3. [3]
    Germa, D. (1989). “Détection de panneaux de STOP.” PSA-ER Internal Report, January.Google Scholar
  4. [4]
    Serra, J. (1982). Image Analysis and Mathematical Morphology. Academic Press, San Diego, California.MATHGoogle Scholar
  5. [5]
    Granger, J. (1990). “Paramètres de formes de contours pour vision par ordinateur.’ PSA-ER Internal Report, January.Google Scholar
  6. [6]
    Baucher F. (1989). “Réalisation d’un Système de Classification Orienté Objet Temps Réel.” PSA-ER Internal Report, June.Google Scholar
  7. [7]
    Granger, C. (1985). “Reconnaissance d’objets par mise en correspondance en vision par ordinateur.” PhD. Thesis, Université de Nice.Google Scholar
  8. [8]
    Zadeh, L. A. (1978). “Fuzzy Sets as a Basis for a Theory of Possibility.” Fuzzy Sets and Systems 1, 3–28.MathSciNetMATHCrossRefGoogle Scholar
  9. [9]
    Reilly, D. L., Cooper, L. N., and Elbaum, C. (1982). “A Neural Model for Category Learning.” Biological Cybernetics, 45, 35–41.CrossRefGoogle Scholar
  10. [10]
    Nestor, Inc. (1990). “Introduction to Nestor Development System NDS.” Manufacturer manual, Providence, Rhode Island.Google Scholar

Copyright information

© Springer-Verlag New York, Inc. 1992

Authors and Affiliations

  • Marie de Saint Blancard

There are no affiliations available

Personalised recommendations