Detection and Recognition of Traffic Sign Boards using Random Forest Classifier

The traffic sign recognition system is a vital aspect of an intelligent transportation since it provides information to drivers help them drive more safely and effectively. This paper addresses some these concerns, which will be accomplished in two steps. first the detection signs, divided into stages. After picture has been preprocessed emphasize relevant information, signs are segmented based on color thresholding, shape-based detection. second task signs. There steps involved this method. In study, Histogram Oriented Gradient utilized as feature extractor, Random Forest Classifier used stage. findings experiment show that utilizing resulted accuracy score 95.59 %, precision 97.55 recall 95.37% process 90.34 % process.