By Topic

Robust on-vehicle real-time visual detection of American and European speed limit signs, with a modular Traffic Signs Recognition system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Moutarde, F. ; Ecole des Mines de Paris (ParisTech), Paris ; Bargeton, A. ; Herbin, A. ; Chanussot, L.

In this paper, we present robust visual speed limit signs detection and recognition systems for American and European signs. Both are variants of the same modular traffic signs recognition architecture, with a sign detection step based only on shape-detection (rectangles or circles), which makes our systems insensitive to color variability and quite robust to illumination variations. Instead of a global recognition, our system classifies (or rejects) the speed-limit sign candidates by segmenting potential digits inside them, and then applying a neural network digit recognition. This helps handling global sign variability, as long as digits are properly recognized. The global sign detection rate is around 90% for both (standard) U.S. and E.U. speed limit signs, with a misclassification rate below 1%, and not a single validated false alarm in >150 minutes of recorded videos. The system processes in real-time videos with images of 640times480 pixels, at ~20 frames/s on a standard 2.13 GHz dual-core laptop.

Published in:

Intelligent Vehicles Symposium, 2007 IEEE

Date of Conference:

13-15 June 2007