Early Model of Traffic Sign Reminder Based on Neural Network

Budi Rahmani (STMIK Banjarbaru)
Supriyadi Supriyadi (STMIK Banjarbaru)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 10, No 4: December 2012

Recognizing the traffic signs installed on the streets is one of the requirements of driving on the road. Laxity in driving may result in traffic accident. This paper describes a real-time reminder model, by utilizing a camera that can be installed in a car to capture image of traffic signs, and is processed and later to inform the driver. The extracting feature harnessing the morphological elements (strel) is used in this paper. Artificial Neural Networks is used to train the system and to produce a final decision. The result shows that the accuracy in detecting and recognizing the ten types of traffic signs in real-time is 80%.