Automatic License Plate Recognition (ALPR) using YOLOv5 model and Tesseract OCR engine

Traffic control and identifying vehicle owners are significant national problems. It could be difficult to identify motorists who drive too quickly and in violation of the law. Since the vehicle's license plate could not be accessible to traffic authorities from a moving vehicle due to its speed, it is impossible to detain and punish those people. Designing an automatic number plate recognition (ANPR) system is one of the solutions to this issue. There are many ANPR systems on the market right now. Although these systems are based on many techniques, it is still tricky work since various elements, such as a vehicle's rapid speed, non-uniform number plate, language of the number, and changing lighting circumstances, can significantly impact the overall identification rate. The majority of the systems function with these restrictions. The characteristics of picture size, success rate, and processing time are discussed in this work along with several ANPR strategies. An ANPR expansion is proposed at the paper's conclusion.