Intelligent Pedestrian Crossing System at Urban Intersection based on Machine Vision Intelligent Recognition System

Urban intersections are important places where pedestrians and vehicles meet, and pedestrian crossing safety has become a key issue. An intelligent pedestrian crossing system based on a machine vision intelligent recognition system is proposed as a solution to improve pedestrian traffic safety and street crossing experience. This study uses a machine vision algorithm model, combined with image and video processing technology, to design and implement an intelligent pedestrian crossing system at an urban intersection. Experimental testing and performance evaluation of the system were conducted, focusing on key indicators such as pedestrian detection and recognition accuracy, signal light status recognition accuracy, and system response time. Experimental results show that the pedestrian detection and recognition accuracy of this system is between 88% and 95%. The pedestrian intelligent crossing system shows high accuracy in pedestrian detection and recognition accuracy, and can accurately calibrate the position of pedestrians and Identify their identity information. The system also shows a high accuracy in the signal light status identification task and can accurately determine the current signal light status. In addition, the system has a short reaction time and can take necessary actions and decisions in time to ensure pedestrians cross the street safely.