Vehicles Number Plate Recognition Systems A Systematic Review

Automatic number plate recognition system (or ANPR) is a system that uses optical character recognition to read characters from solid images automatically and immediately and then convert them to ASCII characters readable by machines. Such a system has been widely used to recognize vehicles plate by using several algorithms and methodologies, including optical character recognition, convolutional or deep neural network, morphological operations, and edge detection. This study aims at understanding and analyzing the concept of the vehicle number plate recognition system, especially those systems which don’t need any human resources to accomplish their missions. For this purpose, this paper presents an analytical and theoretical comparison between several previous works in this field. According to this study, there are different levels of the recognition process starting from collecting images by cameras, detecting the region of plate numbers, segmenting the characters individually, comparing each number with the stored database, and ending with detected the whole plate number. The performance is evaluated based on different factors such as accuracy, precision, and recall.