TAF PUBLISHING

In this research, the detection of traffic signs based on the feature extraction vector and using support machine vector classifiers and neural networks has been done. In this project, we intend to use methods to identify and reset traffic signs. In this study, a fast and robust method for detecting symptoms using algorithms in machine vision is presented. The classification and recognition of signs is also done using smart classifiers such as neural network and vector machine support. To get the right result, we categorize traffic signs into different categories such as mandatory signs or warning signs. The proposed model for recognizing traffic signs consists of two parts. The first part has the task of identifying the type of sign according to the categories done. And the second part is responsible for identifying the type of sign in each of the categories obtained from the first part.