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.
Keywords: traffic sign recognition; advanced driver assistance systems; I2V; computer vision
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García-Garrido, M.A.; Ocaña, M.; Llorca, D.F.; Arroyo, E.; Pozuelo, J.; Gavilán, M. Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System. Sensors 2012, 12, 1148-1169.
García-Garrido MA, Ocaña M, Llorca DF, Arroyo E, Pozuelo J, Gavilán M. Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System. Sensors. 2012; 12(2):1148-1169.
García-Garrido, Miguel A.; Ocaña, Manuel; Llorca, David F.; Arroyo, Estefanía; Pozuelo, Jorge; Gavilán, Miguel. 2012. "Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System." Sensors 12, no. 2: 1148-1169.