Challenges in Automatic License Plate Recognition System Review - Mustafa, Twana; Karabatak, Murat (Institute of Electrical and Electronics Engineers Inc., 2023)
Nowadays, processing vehicle license plate data has become a common and challenging subject of research in Image Processing and Artificial Intelligence. There are various methods proposed to address this problem due to the different shapes and sizes of license plates in different countries. License plate recognition can be used for different purposes, including parking lots, public and private entrances, traffic monitoring systems, cargo control in airports or harbours, and security issues such as finding stolen cars. The technology for license plate recognition is known by different names, including automatic number-plate recognition, automatic vehicle identification, car license plate recognition, and optical character recognition for cars. This technology converts image data from a camera into a character format that can be processed in a database for specific applications. Optical character recognition methods can identify the characters on license plates with great accuracy. The main objective of this paper is to provide a systematic literature review of the most common challenges and methods used for optical character recognition in automated number plate recognition systems, as well as their level of recognition accuracy. © 2023 IEEE.
11th International Symposium on Digital Forensics and Security, ISDFS 2023 -- 11 May 2023 through 12 May 2023 -- TN -- 189042
Keywords: ANPR; Computer vision; Deep learning; External factors; Internal factors; OCR; OpenCV