TY - GEN
T1 - Traffic sign recognition using ridge regression and OTSU method
AU - Jiang, Yanhua
AU - Zhou, Shengyan
AU - Jiang, Yan
AU - Gong, Jianwei
AU - Xiong, Guangming
AU - Chen, Huiyan
PY - 2011
Y1 - 2011
N2 - This paper presents an approach to detect and recognize traffic signs present in the urban scenes in China. The algorithm is composed of three steps that are color segmentation, shape detection and pictogram recognition. In the first step Ridge Regression is used to obtain a precise segmentation in RGB color space and achieves the same good performance as many machine learning based methods while using less computation time. Recognition process include a novel feature extraction involves OTSU method, and the feature extracted is robust against illumination variations and distortions. The algorithm has been run on several thousands of images with promising results.
AB - This paper presents an approach to detect and recognize traffic signs present in the urban scenes in China. The algorithm is composed of three steps that are color segmentation, shape detection and pictogram recognition. In the first step Ridge Regression is used to obtain a precise segmentation in RGB color space and achieves the same good performance as many machine learning based methods while using less computation time. Recognition process include a novel feature extraction involves OTSU method, and the feature extracted is robust against illumination variations and distortions. The algorithm has been run on several thousands of images with promising results.
UR - http://www.scopus.com/inward/record.url?scp=79960817732&partnerID=8YFLogxK
U2 - 10.1109/IVS.2011.5940440
DO - 10.1109/IVS.2011.5940440
M3 - Conference contribution
AN - SCOPUS:79960817732
SN - 9781457708909
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 613
EP - 618
BT - 2011 IEEE Intelligent Vehicles Symposium, IV'11
T2 - 2011 IEEE Intelligent Vehicles Symposium, IV'11
Y2 - 5 June 2011 through 9 June 2011
ER -