Traffic sign recognition is a well-researched problem in computer vision. However, the state of art methods works only for frequent classes, which are well represented training datasets. We consider task rare traffic detection and classification. aim to solve that by using synthetic data. Such data obtained embedding images signs real photos. propose three making consistent with scene appearanc...

TSR (Traffic sign recognition) is an important problem in ITS (intelligent traffic system), which is being paid more and more attention for realizing drivers assisting system and unmanned vehicle etc. TSR consists of two steps: detection and recognition, and this paper describe a new traffic sign detection method. The design principle of the traffic sign is comply with the visual attention mech...

Abstract—To ensure a smooth and secure flow of traffic, road signs are essential. A major cause accidents is negligence in viewing the Traffic signboards interpreting them incorrectly. The proposed system helps recognizing sign sending voice alert through speaker to driver so that he/ she may take necessary decisions. trained using Convolutional Neural Network (CNN) which traffic image recognit...

Now autonomous driving is a hot topic, and the identification of traffic signs also extremely important for driving. This paper mainly compares difference Support Vector Machine (SVM), Multilayer Perceptron (MLP), Logistic Regression (LR) Classifier in sign classification. The effect initial image processing on classification accuracy studied. found that sharpening significantly improved Based ...

The conspicuity of traf ic signs is crucial, as their purpose to give drivers with direction and information. ef ectiveness iciency a sign determined by its visibility, legibility, veracity information for observers. This study recruited primarily postgraduate students participants. assessment was conducted part controlled experiment. Method used in this research indoor experiment using visual ...