A new traffic sign recognition method for intelligent vehicles A new traffic sign recognition method for intelligent vehicles
Résumé
Traffic sign recognition is one of the main components of intelligent transportation systems (ITS). It improves safety by informing the driver of the current state of the road, e.g. warnings, prohibitions, restrictions and other information useful for driving. This paper presents a new road signs recognition method which is achieved in three main steps. The first step maps the input image from the Cartesian coordinate system to the log-polar one. The second step computes histogram of oriented gradients (HOG), local binary pattern (LBP) and local self-similarity characteristics (LSS) from the image represented in the log-polar coordinate system. The third step performs the classification on the basis of the random forest classifier and the features computed in the second step. The proposed method has been tested on the German Traffic Sign Recognition Benchmark dataset and the results obtained are satisfactory when compared to the state of the art approaches.