7A-5-1
Traffic Sign Detection from Image Sequences
W. B. Tong J. Y. Hervé P. Cohen
Groupe de Recherche en Perception et Robotique
Ecole Polytechnique de Montréal
Montréal (Québec), Canada, H3C 3A7
Abstract
This paper describes automatic traffic sign detection
based on colorT shape and text information of traf
fic signs for mobile mapping. Vision technologies are
applied to extract georeferenced data to build a geo
graphic information system. This gives georeferenced
traffic signs data for use in a highway pavement man
agement system. 1
1 Introduction
Geographic Information Systems (GIS) have many ap
plications. An example is map-making [1] for highway
and transportation infrastructure with the identifica
tion and location of road signs based on stereo vision
and on Global Position System (GPS) technologies.
To collect dataT vehicles like the one illustrated in
Figure 1 are used. This one basically consists of a
GPS and a stereo camera system mounted on a van.
While the van is traveling at a normal traffic speedrthe
stereo camera system records stereo video sequences
for a roadway. Each video frame is tagged with the
GPS signal and geodetic coordinates: latitude, longi
tude and ellipsoidal height. The video sequences are
post-processed to detectridentifyTand locate road fea-
turesTfor instancerroad edges and traffic signs.
Existing mobile mapping systems typically run
with an operator interactively clicking on objects of
interests in video sequences to show the system where
the object is and what it is. To speed up data col
lection and reduce operator workloadTit is natural to
develop an automated system for GIS objects extrac
tion from video sequences.
1 This research work is supported by the National Research
Council of Canada and in collaboration with GIE Technologies
Inc.
Figure 1: A van with a stereo camera system and GPST
courtesy: the Lambda Company
2 Related works
At the Image Recognition LaboratoryT Universität
KoblenzrGermanyra real time traffic sign recognition
system has been developed in cooperation with Daim
ler Benz as part of the European PROMETHEUS
project (Program for a European Traffic with High
est Efficiency and Unprecedented Safety) [4]. For re
altime analysisTthis system employs special hardware
to process traffic images. In the same projectTat the
Ulm Research center of Daimler-Benz AGTa hybrid
approach has been developed for traffic sign recogni
tion. It involves color segmentation with a pixel clas
sifier and a pictogram classifier [5].
At the Department of Electrical EngineeringlTexas
A. & M. UniversityT USATa traffic sign recognition
system [3] has been developed to alert drivers of ap
proaching warning signs: ‘stop’FyieldTand ‘don’t en-
terTetc.
A robust road detection and recognition systemT
developed at the University of GenovaTworks in three
stages. The first stage reduces the search of a road
sign to a subregion of the image using a priori knowl
edge of the scene or color clues. The second stage
geometrically analyzes edges extracted from images
to identify regular sign shapes. The last stage uses
a cross-correlation technique to recognize traffic signs
[2].
