DocumentCode :
2661083
Title :
Neural traffic sign recognition for autonomous vehicles
Author :
de la Escalera, A. ; Moreno, L. ; Puente, E.A. ; Salichs, M.A.
Author_Institution :
Dept. de Ingenieria, Univ. Carlos III, Madrid, Spain
Volume :
2
fYear :
1994
fDate :
5-9 Sep 1994
Firstpage :
841
Abstract :
A vision-based vehicle guidance system working in road environments has three main roles: road detection, sign recognition, and obstacles detection. Traffic signs provide very valuable information about the road in order to provide safer and easy driving environment. Traffic signs are designed to be easily recognized by human drivers mainly because their colors and shapes are very different from natural environments. The algorithm presented in this paper makes the best use of these features. The algorithm has two main parts: 1) for detection using the colors and shapes of the signs; and 2) for classification using a neural network
Keywords :
colour; computer vision; image recognition; navigation; neural nets; road vehicles; autonomous vehicles; color recognition; image classification; neural network; shape recognition; traffic sign recognition; vision-based vehicle guidance system; Humans; Image edge detection; Mobile robots; Neural networks; Remotely operated vehicles; Road vehicles; Shape; Telecommunication traffic; Vehicle detection; Vehicle driving;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, Control and Instrumentation, 1994. IECON '94., 20th International Conference on
Conference_Location :
Bologna
Print_ISBN :
0-7803-1328-3
Type :
conf
DOI :
10.1109/IECON.1994.397896
Filename :
397896
Link To Document :
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