DocumentCode :
3465147
Title :
Robust recognition of traffic signals
Author :
Lindner, Frank ; Kressel, Ulrich ; Kaelberer, Stephan
Author_Institution :
Res. & Technol., Daimler-Chrysler AG, Ulm, Germany
fYear :
2004
fDate :
14-17 June 2004
Firstpage :
49
Lastpage :
53
Abstract :
In this paper a general system for real-time detection and recognition of traffic signals is proposed. The key sensor is a camera installed in a moving vehicle. The software system consists of three main modules: detection, tracking, and sample-based classification. Additional sensor information, such as vehicle data, GPS, and enhanced digital maps, or a second camera for stereo vision, are used to enhance the performance and robustness of the system. Since the detection step is the most critical one, different detection schemes are compared. They are based on color, shape, texture and complete-object classification. The color system, with a high dynamic range camera and precise location information of the vehicle and the searched traffic signals, offers valuable and reliable help in directing the driver´s attention to traffic signals and, thus, can reduce red-light running accidents.
Keywords :
cameras; image colour analysis; image recognition; object detection; road accidents; road vehicles; signal detection; tracking; traffic engineering computing; camera; image color analysis; moving vehicle; object classification; real time detection; real time recognition; red-light running accidents; robust recognition; sample based classification; sensor information; stereo vision; tracking; traffic engineering computing; traffic signals; Digital cameras; Dynamic range; Global Positioning System; Real time systems; Robustness; Sensor systems; Shape; Software systems; Stereo vision; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2004 IEEE
Print_ISBN :
0-7803-8310-9
Type :
conf
DOI :
10.1109/IVS.2004.1336354
Filename :
1336354
Link To Document :
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