@article{sensors:garrido2012,
author = "Garrido, Miguel {\'A}ngel G. and Oca{\~n}a, Manuel and Llorca, David F. and Arroyo, Estefan{\'i}a and Pozuelo, Jorge and Gavil{\'a}n, Miguel",
abstract = "This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.",
issn = "1424-8220",
journal = "Sensors",
number = "2",
pages = "1148--1169",
title = "{C}omplete {V}ision-{B}ased {T}raffic {S}ign {R}ecognition {S}upported by an {I}2{V} {C}ommunication {S}ystem",
url = "http://www.mdpi.com/1424-8220/12/2/1148/",
volume = "12",
year = "2012",
}