Several complex problems have to be solved in order to build Advanced Driving Assistance Systems. Among them, an important problem is the detection and classification of traffic signs, which can appear at any position within a captured image. This paper describes a system that employs independent modules to classify several prohibition road signs. Combining the predictions made by the set of classifiers, a unique final classification is achieved. To reduce the computational complexity and to achieve a real-time system, a previous input feature selection is performed. Experimental evaluation confirms that using this feature selection allows a significant input data reduction without an important loss of output accuracy.
['M. P. Sesmero', 'Juan Manuel Alonso-Weber', 'G. Gutiérrez', 'Agapito Ledezma', 'Araceli Sanchis']
Specialized ensemble of classifiers for traffic sign recognition