License plate recognition technology becomes one of the tools of advanced modern monitoring and security systems. Although the technology’s primary application is related to vehicle identification, its applications are now rapidly expanding to include areas such as politics.
Key Functions of License Plate Recognition Technology
These systems are primarily used in areas such as vehicle flow control, law enforcement processes, and payment processing control. However, continuous technological progress is expanding the capabilities and scope of such tools.
The main application of this technology is associated with identifying and tracking vehicle owners. Typically, cameras are used to capture the vehicle’s license plate information, and the software then compares the captured image with a database of license plate numbers. As mentioned, it can also be utilized for other purposes.
When examining the operating principle in detail, it can be broken down into several stages: image acquisition, pre-processing, character segmentation, recognition, and further processing. It is important to note that the image captured by the camera is passed through optical character recognition (OCR) technology and image processing tools.
OCR is necessary to convert the captured number into characters that can be compared with database information. Meanwhile, algorithms analyse the images and check their matches against the database, ultimately leading to recognition.
The cameras used for capturing images can be of two types: infrared and visible light. The first type is suitable for capturing images in poorly lit conditions, while the second is more effective during the day but can capture significantly more detailed information than the first.
Broader Applications of License Plate Recognition Technology
LPR systems enable access control functionality, making them useful in parking management when there is a closed parking lot, various gates, etc. This process of entering a space is automatically controlled.
In traffic management processes, this technology can help monitor traffic flows. In law enforcement, number plate recognition assist in the search for stolen vehicles and are used in the pursuit of suspects. In retail, LPR can be used to determine when people leave premises without paying.
Moreover, this identification method can be applied in a slightly different area. One study investigated how facial recognition technology could be used to identify political orientation. The research was based on natural facial images from which datasets were created featuring different political beliefs.
Consequently, algorithms analysed facial features: symmetry, proportions, skin texture, expressions, and established potential correlations. The conclusion indicated that certain facial features may correlate with political views. Therefore, such aspects could be used in the future to analyse political behaviour patterns, create predictions, and identify potential threats in political discourse.
One innovative technology example is Neurotechnology, which offers one of the advanced video analysis and surveillance solutions, SentiVeillance, featuring algorithms for face recognition, vehicle-human interaction, and automatic license plate recognition. These algorithms can successfully automate security checks, monitor road traffic safety, ensure public order by authorities, or be used in parking management while allowing the creation of unique recognition products with a pre-developed software toolkit.
Final Word
The fact that these solutions are not just theoretically described but are already being utilized and developed, as evidenced by the Neurotechnology case, demonstrates that license plate information can significantly transform certain important societal areas and ensure the effective functioning of specific processes. Nevertheless, it is essential to remember that these advancements are not solely positive. They also pose certain challenges in the realm of data protection that will increasingly become apparent and must be addressed.
Sources: SentiVeillance, Sensor Dynamics, Nature Portfolio
