Publicado en International Conference on Systems, Signals, and Image Processing Abstract: This paper describes an implemented solution to automatically detect and recognize in real-time both speed limit warning signs and speed limit signs in railway travel videos recorded from the driver's cab. The lack of available high-quality videos to train this kind of systems and the involved complexity of the rail scenes, with non-controlled illumination conditions, make it challenging the considered problem. Our framework achieved interesting recognition results of around 95% for both signs types and digits recognition.

GAVAB es un grupo multidisciplinar formado por profesores de la Universidad Rey Juan Carlos que recoge diferentes líneas de investigación encuadradas en el área de conocimiento de las Ciencias de la Computación y de la Inteligencia Artificial.