The license plate is considered a kind of identification of vehicles. A glance at the license plate gives you a lot of information, from the history of damage to the car to the policy information. In order to be able to read the license plate, license plate recognition systems or PTS (License Plate Recognition System) have been developed for short.
These systems recognize the characters on the license plate using optical character recognition techniques by processing the images they receive from the cameras.
License plate recognition systems, known as ALPR (Automatic License Plate Recognition), make it easier to find stolen, foreclosed or stolen vehicles. PTS, which is an important part of the security system, is used in many places. This includes Mobile cameras.
License plate recognition systems are defined as systems designed to read license plates from any vehicle. License plate readings are based on software because they are made by taking a digital image. They are usually used for vehicle tracking. Thanks to the license plate recognition system, successful license plate recognition for each vehicle not only provides a high level of comfort, but also gives results that are worth seeing. Reading the plates manually makes them old-fashioned, while they are effective in providing the desired convenience in terms of practical features. The license plate recognition system is always available. It is possible to read vehicles regardless of their make and model as long as they have license plates.
What is the Principle of Operation of License Plate Recognition Systems?
The license plate recognition system is very easy to use. In particular, the area where the license plate is located is highlighted in the image captured by the camera of the vehicle. The license plate image is processed by the software used. The reading is done. The measured value provided by the software is compared with the database. Although the operating system of the license plate recognition system is simple in practice, it is quite complex in content.
