LPR uses optical character recognition to scan plates at high speed. The software isolates and captures vehicle plates and logs registration marks with time, date and GPS. It interprets and transfers this information from analogue to digital, and then cross-references letters and numbers with predetermined databases to enable automatic alerts for specific vehicles.

License plate recognition can be used for a variety of functions. For parking lots, LPR can be used to identify cars that already have a parking subscription and should therefore be granted access. Similarly, select license plates can also be added to a blacklist in order to deny access or send a notification once blacklisted licenses are read. For law enforcement, LPR can also be helpful with tracking suspected criminals or even for regulating speeding on roads or highways. Lastly, LPR can also be useful for companies who deal with cars as part of their business operations, for example fuel stations would be able to recognize cars that have been blacklisted and shut down pumps before they are used.

There are a few factors that will ensure you get the most out of your LPR camera system. First there’s the quality of the cameras that you are using. The better the input (imaging), the better your LPR software will be able to accurately recognize and identify the license plates. This is especially true when vehicles are traveling at high speeds or in low-light areas. Secondly is the speed with which the software can run and process the input from the camera. The faster it can identify the license plate, the better. And lastly, you should also consider how many recognition algorithms the LPR software supports. The more countries are supported, the higher the chances are that the vehicles you will be tracking will be recognized in the areas that you are monitoring.

License plate recognition accuracy can vary based on several factors including the quality of the cameras, lighting conditions, the speed of the vehicles and the complexity of the license plate design. Generally, modern LPR systems can achieve high accuracy rates, often exceeding 90% under optimal conditions.

The steps involved for LPR include capturing vehicle images using cameras, processing them to enhance quality and locating license plate regions. The characters on the license plate are then recognized using algorithms. The results are then refined and decisions are made based on recognition, such as logging license plate information or triggering alerts. The recognized data can be integrated with databases for various applications like law enforcement, toll collection and access control. LPR systems employ image processing, pattern recognition and machine learning to automate license plate information extraction from images.

XProtect LPR supports optimized recognition algorithms for more than 200 countries. It is designed to be compatible with various license plate formats from different regions. It supports license plate recognition for standard alphanumeric plates, as well as specialized formats such as Arabic, Cyrillic, Chinese, and Japanese characters. Additionally, it can read license plates with different sizes, colors, and fonts. However, the specific compatibility may vary depending on the version and configuration of the software, so it's advisable to consult the official documentation or contact Milestone Systems for detailed information regarding compatibility with specific license plate formats.