ANPR is defined as the technology to identify a vehicle through the number plate it uses. Using recognition cameras, the technology is able to scan a sign and forward the required action to the system that manages the entrance. This enables modernized vehicle access control and reduces the need for manpower, given the autonomous operation offered.

The technology has seen significant growth in recent years due to the range of benefits it offers in a range of different applications. After all, these systems are among the most accurate and widely used computer vision solutions, and the applied methods are constantly evolving to enhance the performance, accuracy, efficiency and scalability of the associated software. The use of ANPR systems is becoming even more popular as technology advances rapidly with the advent of artificial intelligence, machine learning and deep learning, with computational costs decreasing and the accuracy of applied image processing techniques increasing.

There are a number of different techniques that are widely used in the adoption of machine vision technologies. The most important components of such a system are real-time object detection (which uses deep learning to identify vehicles and categorize them, such as buses, cars, trucks, motorcycles, etc.), making use of streaming video. Object detection algorithms, in turn, exploit neural networks trained on datasets. This is followed by processing with traditional methods (computer vision) used to prepare images that will be processed by the OCR algorithm. Since ANPR applications are usually implemented in challenging real-world environments with varying lighting, weather conditions, and inconsistent settings, image processing is used to contribute to enhancing sharpness, color correction, or even cropping photos, aiming improving the final result.

Next is optical character recognition (OCR), a computer vision technique for reading text in images, which allows an ANPR system to recognize license plates. Algorithms such as OCR are used to detect individual characters, verify the sequence and convert the image to text. Pattern matching, on the other hand, is a comparison technique that uses libraries to find matches. Pattern matching is a technique that aims to find patterns. In the case of ANPR, the set of characters are license plates.

Also, in some situations, such as at night, these cameras may produce images where additional details are not visible. However, license plates are always “captured” in such a way that the ANPR software can easily interpret them and convert them to the required ASCII or Unicode format. Speaking of ANPR, the most advanced cameras support built-in license plate recognition either natively through an integrated processing unit or through a cloud connection so that captured images are forwarded to end users with license plate data already attached to the data package

From all of the above, it is clear that a number of advantages arise. Most of the benefits of ANPR come from automating manual tasks and highly efficient space management. License plate recognition enables automated alerts and checks. Therefore, ANPR systems are a key technology for the increasingly growing smart cities. They offer high accuracy through easy and fast vehicle identification.

At the same time, they are also an important source of analytics, as the resulting data can be used for traffic analyses. This is particularly important for the operation of Intelligent Transport Systems, where data processing technologies are adopted to improve the mobility of people and goods, manage demand, increase safety, reduce traffic congestion and effectively manage incidents. At the same time, it is clear that long numbers are analyzed very quickly, making ANPR a very effective method that leads to better control of finances and a reduction in waiting times.

Finally, the system offers flexibility as automated license plate recognition can be implemented for a variety of applications. Systems of this type help to improve safety by providing a method for autonomously locating and tracking multiple vehicles as well as a number of environmental benefits. Using an ANPR system can help reduce traffic congestion and pollution by discouraging unnecessary travel. Reducing the time of waiting and the time of searching for parking spaces also contributes to the reduction of environmental pollution.