Lebanese automated number plate reading based on neural network recognition

In this paper, a license plate recognition technology will be addressed in regards to the following components: image preprocessing, segmentation and recognition of plates' numbers. This technology allows recognizing license plates efficiently with day and night time images. Automatic number plate recognition (ANPR) system is a part of intelligent transport systems due to its efficient applications in areas such as highway electronic toll collection, traffic monitoring system, parking management, parking fee and so on. The article will delineate an automatic (programmed) neural network recognition system of auto license plates that was connected in numerous nations and our capacity to utilize this framework on Lebanese auto tags. This system depends on the extraction of the license plate, segmentation (division) of characters [1], and neural network optical character recognition (NNOCR) subsequent to catching a picture of the vehicle tag by a computerized camera. Applying this system in Lebanon will increase performance and security of the public parking as well as collecting parking fees without the need of utilizing the electronic card [2].