By Topic

Robust traffic sign recognition and tracking for Advanced Driver Assistance Systems

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)
Zhihui Zheng ; Minist. of the Sch. of Autom., Beijing Inst. of Technol., Beijing, China ; Hanxizi Zhang ; Bo Wang ; Zhifeng Gao

In this paper we propose a traffic sign recognition system using an on-board single camera for Advanced Driver Assistance Systems (ADAS), including detection, recognition and tracking. We combine RGB ratios based color segmentation with automatic white balance preprocessing and Douglas-Peucker shape detection to establish ROIs. Scale and rotation invariant BRISK features are applied for recognition, matching the features of the candidates to those of template images that exist in database. Tracking-Learning-Detection (TLD) framework is adopted to track the recognized signs in real time to provide enough information for driver assistance function. This paper presents lots of experiments in real driving conditions and the results demonstrate that our system can achieve a high detection and recognition rate, and handle large scale changes, motion blur, perspective distortion and various illumination conditions as well.

Published in:

Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on

Date of Conference:

16-19 Sept. 2012