Image processing based traffic sign detection and recognition with fuzzy integral - Taştimur, Canan; Karaköse, Mehmet; Çelik, Yavuz; Akin, Erhan (IEEE Computer Society, 2016)
Todays, the number of vehicles is rapidly increasing. In parallel, the number of ways and traffic signs have increased. As a result of increased traffic signs, the drivers are expected to learn all the traffic signs and to pay attention to them while driving. A system that can automatically recognize the traffic signs has been need to reduce traffic accidents and to drive more freely. Traffic sign recognition system meet this need. This study includes traffic sign detection and recognition application. In this study, some image processing techniques are used to detect traffic signs and Fuzzy Integral is used to recognize traffic signs. Both more accuracy rate results and low computational cost are obtained in terms of recognition stage by using positive aspects of algorithms taken as input parameters with Fuzzy Integral in the traffic sign recognition system. Experimental results show that proposed method gives high accurate results in a reasonable time. © 2016 IEEE.
23rd International Conference on Systems, Signals and Image Processing, IWSSIP 2016 -- 23 May 2016 through 25 May 2016 -- Bratislava -- 122534
Keywords: Color and Shape Segmentation; Fuzzy Integral; Image Processing; Traffic Sign Recognition