License Plate Recognition for Traffic Management

Abstract

The objective of this report is to present an overview of the project, license plate recognition. This system is to basically detect a vehicle using the information of the license plate in order to use the information at various valid sites. This tool can work as a part of other big projects in the industry for security purposes as well as for analysis purposes. There is a detailed insight of the project in several different chapters throughout the report. This project is based on detection and recognition algorithms; using several libraries of python to work on images and videos and thereafter using the processed image to further train and test a model using machine learning algorithm such that the recognition is done with higher accuracy. The beginning outlines the introduction to the topic and its importance in the real world by highlighting some other applications using similar approach. Later it highlights the technology and skills in use in order to completely deploy the idea. Further there is an explanation to the feasibility study as well as the requirement specification while system design revolves around the basic designing of several modules which would integrate to work as the whole system and test cases. Implementation and testing approach is being discussed and thereby light has been thrown on the results and conclusion thus bringing attention to system’s limitation and its future scope.

License Plate Recognition System Based on Artificial Intelligence with Different Approach

“…Singh and Singh [25] developed LPRS using machine learning algorithms and Python programming language in India, and their system worked at 96% accuracy. Guan et al [26] developed an LPRS based on capsule networks in their study.…”