Deep Learning Based License Plate Number Recognition for Smart Cities

Smart city-aspiring urban areas should have a number of necessary elements in place to achieve the intended objective. Precise controlling and management traffic conditions, increased safety surveillance, enhanced incident avoidance be top priorities smart city management. At same time, Vehicle License Plate Number Recognition (VLPNR) has become hot research topic, owing several real-time applications like automated toll fee processing, law enforcement, private space access control, road surveillance. Automated VLPNR is computer vision-based technique which employed recognition automobiles based on vehicle plates. The current paper presents an effective Deep Learning (DL)-based called DL-VLPNR model identify recognize alphanumeric characters present license plate. proposed involves two main stages namely, plate detection Tesseract-based character recognition. takes with help fast RCNN Inception V2 model. Then, detected are extracted using Tesseract Optical Character (OCR) performance was tested this benchmark databases, experimental outcome established superior compared other methods.