Computer Vision based License Plate Detection for Automated Vehicle Parking Management System

With proliferation of vehicles across the world, it is getting increasingly strenuous to manage parking in several spaces viz business parks, residential complexes, shopping malls etc. An optimum utilization of available parking spaces and minimizing the time and effort involved in vehicle parking, an integrated and automated vehicle parking management system (VPMS) is necessitated. License plate contains relevant information about vehicle and its detection & recognition in real time can be utilized to develop an automated VPMS. In this paper, a solution is proposed for live detection and recognition of a moving vehicle's license plate number using Computer Vision techniques. Three different models had been studied viz HAAR cascade and CNN1, OpenCV2 and YOLOv3 with OpenCV3 to find the best performing model. Among these, YOLOv3 with OpenCV outperforms other models due to its ability to detect the rectangular bounding boxes with great accuracy. The automation of license plate detection is a two-step process which includes detection of custom object i.e License plate using YOLOv3 and recording/processing the number plate details using Open CV algorithms. The trained model is validated and demonstrated 100% accuracy in detection of license plate bounding boxes along with 95% accuracy in text recognition. This module can be implemented and integrated with other add-on systems for effective usage in various sectors.