Automatic License Plate Recognition

Automatic license plate recognition using Image processing offer students a unique opportunity to gain hands-on experience in designing and optimizing the Embedded system. This typically involve working with industry professionals on actual projects, providing interns with valuable exposure to real-world challenges and best practices in the field of Embedded system. During the project, participants are often tasked with designing using specialized software tools like MATLAB. In recent times, the number of vehicles on road has exponentially risen due to which traffic congestion and violations are a menace on roads. Automatic License Plate Recognition (ALPR) system can be used to automate the process of traffic management thereby easing out the flow of traffic and strengthening the access control systems. In this paper, we compare the efficiency achieved by morphological processing and edge processing algorithms. A detailed analysis and optimization of neutral network parameters such as regularization parameter, number of hidden layer units and number of iterations is done. The system utilizes image processing techniques and machine learning algorithms running on MATLAB and Arduino to obtain the results with an efficiency of 97%. The system was tested on a set of static images as well as in a dynamic environment. The execution time of the system on a dynamic environment and the license plate of the vehicle can be identified as well. In addition to technical skills, interns gain exposure to the latest industry trends and technologies, preparing them for future roles in the Embedded of electronics industries. The mentorship and networking opportunities available during the project can lead to valuable connections and potential job offers after graduation. Keywords: License Plate Recognition, Morphological Operations, Character Segmentation, Template Matching, Sobel Filter, AVR Microcontroller