Robust traffic sign recognition and tracking for Advanced Driver Assistance Systems

Zhihui Zheng*, Hanxizi Zhang, Bo Wang, Zhifeng Gao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012
Pages704-709
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012 - Anchorage, AK, United States
Duration: 16 Sept 201219 Sept 2012

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Conference

Conference2012 15th International IEEE Conference on Intelligent Transportation Systems, ITSC 2012
Country/TerritoryUnited States
CityAnchorage, AK
Period16/09/1219/09/12

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