Surveillance Rapid Detection of Signs of Traffic Services in Real Time

Abstract

This study aims to compare the efficiency of Intuitionistic Fuzzy Neural Network with Genetic Algorithm (IFNN-GA) in detecting real-time traffic signs in different road conditions compared with the human eyes in order to prove that they are more efficient in understanding the surrounding environment, support safe driving, and overcome human defects. Highlighting the driver's obstacles such as weather conditions, uneven lighting, shadows everywhere, intensity and brightness fluctuations and contrast in shape and texture of traffic signs and time spent for entry and exit. In order to realize all aspects of the road, a model was proposed: Intuitionistic Fuzzy Neural Network with Genetic Algorithm (IFNN-GA).