German Traffic Sign Recognition Using Convolutional Neural Network

Traffic signs provide the necessary information and warn of possible dangers. Traffic sign recognition plays a crucial role in helping drivers understand signposts, obey traffic rules and develop automated driving systems. This research work has developed a convolutional neural network (CNN) model to classify the traffic signs displayed in the image into different categories, such as speed limits, prohibitions, left or right turns, child crossings, overtaking heavy vehicles, etc. The proposed system can recognize and classify 43 types of signs. The proposed model has achieved an accuracy of 98.81% on test data.