Date of Award
Program or Major
Master of Science
Automated license plate recognition systems make use of machines learning coupled with traditional algorithmic programming to create software capable of identifying and transcribing vehicles’ license plates. From this point, automated license plate recognition systems can be capable of performing a variety of functions, including billing an account or querying the plate number against a database to identify vehicles of concern. These capabilities allow for an efficient method of autonomous vehicle identification, although the unmanned nature of these systems raises concerns over the possibility of their use for surveillance, be it against an individual or group. This thesis will explore the fundamentals behind automated license plate recognition systems, the state of their current employment, currently existing limitations, and concerns raised over the use of such systems and relevant legal examples. Furthermore, this thesis will demonstrate the training of a machine learning model capable of identifying license plates, followed by a brief examination of performance limitations encountered.
Noboa, Nicholas, "Automated License Plate Recognition Systems" (2022). Master's Theses and Capstones. 1654.