License Plate Identification using Machine Learning Techniques

Abstract

Transport is a major part of human life The Internet of things supports a million devices attached and is bringing the social environment around us smarter and more adaptive, integrating the real and digital worlds. Artificial intelligence improves the transportation system up to a great level, such as self-drive vehicles, auto traffic control systems and parking systems, etc. Due to an increase in the Number of vehicles where the facilities increase, vehicle theft is also increasing with the same edge. techniques are used in the literature, but many time accuracy problem while size of plate is minimum, computationally huge expensive and very slow. Here we will develop a system to detect and identify the license plate using Convolutional neural network. we select the license plate area and extract the numbers and alphabets from the license plate. Huge convergence in computer technology has contributed to the treatment in automobiles as a conceptual unit of knowledge networks, in different aspects of the real world. Our proposed system has achieved the accuracy 90.2%.  Since an autonomous computer system is useless without any details, vehicle computer has to be changed between reality and the software system. This research is mainly done to enhance the transportation security management system.