A framework of Malicious Vehicles Recognition in Real Time Foggy Weather

This paper will compare between two frameworks to identify vehicles. The first is a framework that identify malicious vehicles through license plate recognition and communication protocol. The second is a framework that recognize vehicles in foggy weather based on two-step recognition algorithm. The goal is to produce a combined framework of malicious vehicles recognition in foggy weather. The paper will compare between them and extracts conclusions for better combined framework. That framework will combine the positive features of both frameworks in order to recognize malicious vehicles in real time using a camera and algorithms without any human contact. That combination is needed since the outbreak of COVID-19 and the need of least human exposition and contact.