SENSOR ENABLED COLLEGE PARKING SYSTEM









Abstract

Security has always been a priority for humanity. Today we have video surveillance cameras in schools, hospitals and every other public place that make us feel safe. With advances in technology, especially in image processing and machine learning, it is possible to make these cameras smarter by training them to process information from video feeds. In this article we will learn how to identify and read the license plate number from an automobile using Raspberry Pi and OpenCV. We use some random vehicle images from Google and write a program to locate the number plate using OpenCV contour detection, and then read the number from the plate using Tesseract OCR. In areas where parking space is allocated for a specific vehicle, an incorrectly parked vehicle can be identified. The number plates of the vehicle come in different shapes and sizes and they also vary in color. This allows the vehicle to be identified by its number plate. Number plate detection helps detect stolen cars, car parking management systems and vehicles in traffic. In this method all the letters and numbers used in the number plate are sorted using the bounding box method. After splitting, the template matching method is used to identify numbers and letters. The decoded number plate is further used for identification, matching and documentation of vehicle details.


Modules


Algorithms


Software And Hardware