Car plate recognition using machine learning techniques

Abstract

Machine learning, a method of data analysis that automates analytical model building. It is a branch of Artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. In this project, we will be exploring how machine learning is used in car plate recognition and what are the machine learning techniques used to accomplish the recognition capabilities. First chapter will basically consist of introduction and project objective. Second chapter will be the setting up of a virtual machine as this project will be testing out open-source code, using a virtual machine will mitigate the risk of a security breach in the computer. As there are many Linux based OS available, in this project we will be using Fedora OS and with the help of anaconda navigator as our prerequisite manager. There are screenshots and code provided to facilitate a replication of the project procedure to replicate the results. In the Third chapter, the code on how to initialize the pre-trained model, detect the car plate, segment the characters in the car plate, train the character recognition model to perform OCR on the image to produce digitize character, initialize the trained model and output the results