Paper Info
Title
Fast traffic sign detection and recognition under changing lighting conditions
Abstract
In this work a system for traffic-sign detection and classification is shown. It is intended for both prohibition and obligation circular signs and for advertising triangular ones. The system is divided into three stages: first, detection, using the Hough transform from the information of the edges of the image; second, classification, using a neural network, and third, tracking, making use of a Kalman filter, which provides the system with memory. Some results are presented, obtained by real images recorded by only one camera placed on board a conventional vehicle, in sunny days, and also cloudy, rainy ones or at night, in order to show the reliability and robustness of the system. The average processing time is 30 ms per frame, what makes the system a good approach to work in real time conditions
Year
DOI
Venue
2006
10.1109/ITSC.2006.1706843
ITSC
Keywords
Field
DocType
hough transforms,kalman filters,edge detection,image classification,neural nets,traffic engineering computing,hough transform,kalman filter,neural network,traffic sign classification,traffic sign detection,psychology,real time
Computer vision,Simulation,Edge detection,Hough transform,Robustness (computer science),Kalman filter,Artificial intelligence,Real image,Engineering,Artificial neural network,Contextual image classification,Traffic sign detection
Conference
ISBN
Citations 
PageRank 
1-4244-0093-7
33
1.44
References 
Authors
11
6
Name
Order
Citations
PageRank
Garcia-Garrido, M.A.1331.44
Miguel Ángel Sotelo250268.97
Martm-Gorostiza, E.3331.44
Miguel Ángel Garcia422024.41
Miguel Ángel Sotelo Vázquez5342.60
Ernesto Martín Gorostiza6331.44