An Proficient Approach For Number Plate Detection From Vehicle Images By Image Processing


This paper introduces the development of an automated car plate acquisition program using the image processing process. The popular name for this system is Automatic Number Plate Recognition (ANPR). The automatic car license plate system is often used in the field of safety and security systems especially in the parking lot. In addition to the safety feature, this system is used to monitor road congestion such as traffic rule violation and to identify the vehicle owner. The program is developed to help the traffic police in recovering stolen vehicles not only from cars but also from motorcycles. In this program, the OCR process was the primary method used by investigators to analyze the image of a car plate. The limit for this approach was the inability to translate data or text accurately. In addition, characters, background, and plate sizes vary in different country. Therefore, this project proposes a group of image processing and OCR to get accurate vehicle number plate. The result of this program is a system that can accurately locate the letters and numbers of a car plate in various domains (black and white). This research includes the development of a Graphical User Interface (GUI) to enable the user to recognize letters and numbers on a car or on license plates. Keywords: Automatic Number Plate Detection, bilateral filter (iterative), histogram equalization, number plate characters extraction, morphological operations, threshold, detection and removal of edges, component analysis.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL