RT Conference Proceedings
T1 Specialized ensemble of classifiers for traffic sign recognition
A1 Sesmero Lorente, María Paz
A1 Alonso Weber, Juan Manuel
A1 Gutiérrez Sánchez, Germán
A1 Ledezma Espino, Agapito Ismael
A1 Sanchis de Miguel, María Araceli
AB 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.
PB Springer
SN 978-3-540-73006-4
SN 0302-9743
YR 2007
FD 2007
LK https://hdl.handle.net/10016/9937
UL https://hdl.handle.net/10016/9937
LA eng
NO Proceeding of: 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastían, España, junio, 2007.
NO The research reported here has been supported by the Ministry of Education and Science under project TRA2004-07441-C03-C02.
DS e-Archivo
RD 18 may. 2024