How ANPR technology is revolutionizing vehicle identification – Part 2 – The process and benefits
In the second part of our article, we delve deeply into the process of ANPR and it’s benefits.
In the first part of our article, we already briefly explained how the ANPR process works. Now we’ll explore it further.
The ANPR process
ANPR systems combine computer vision, image processing, and machine learning to extract license plate information from images or video frames. This technology has evolved significantly, benefiting from advancements in machine learning, deep learning, and computational efficiency. Its applications range from traffic management to parking enforcement, making it an essential tool in modern-day society.
The process is the following:
1) Real-Time Object Detection
ANPR begins with capturing images or video frames using cameras. These cameras are often equipped with infrared lighting to ensure visibility even at night.
The first step is to detect and localize the license plate within the captured image. Machine learning and computer vision techniques are employed for this task.
Once the license plate is identified, it is cropped from the larger image, isolating it for further processing.
2) Image Processing
In this stage, various image processing techniques are applied to the cropped license plate:
3) Optical Character Recognition (OCR)
OCR is a critical step in ANPR. It involves recognizing the characters on the license plate. The segmented characters are fed into an OCR system, which interprets them as alphanumeric symbols. The OCR system uses pattern recognition algorithms to map these symbols to actual letters and numbers. The result is the extracted license plate number.
4)Template Matching
This step is used to verify the extracted characters.
A database of known license plate templates (patterns) is maintained. The extracted characters are compared against these templates to validate their correctness. If a match is found, the system confirms the accuracy of the recognized license plate.
The benefits of ANPR
ANPR offers a multitude of advantages and benefits. Most of those come from automating manual tasks, highly efficient space management, governance, and increasing the customer experience.
1) Automation and accuracy
Automation lies at the heart of ANPR, streamlining manual tasks and enabling automated alerts and controls for facilities. This makes ANPR pivotal in the infrastructure of smart cities and toll stations. Moreover, ANPR systems boast remarkable accuracy, swiftly identifying vehicles by their license plates. This precision facilitates seamless vehicle identification for access grants or tracking purposes.
2) Analytics
The generated data from ANPR systems fuels traffic flow analytics, key for Intelligent Transportation Systems. Leveraging data processing technologies, ANPR aids in optimizing mobility, demand management, safety enhancement, congestion reduction, and incident management.
3) Cost-efficiency and scalability
Cost-efficiency is a hallmark of ANPR, as its rapid and precise recognition negates the need for human input. This enables swift analysis of a large volume of license plates, driving cost-effective governance and reducing waiting times.
Scalability is further enhanced through the integration with emerging and existing technologies. This facilitates offline capabilities, private video analytics, and cost-efficient operations.
4) Versatility and security
ANPR systems integrate seamlessly with other systems, providing a hassle-free experience for end-users. The versatility of ANPR extends to various applications, including parking management, security, traffic enforcement, and logistics.
From a security standpoint, ANPR solutions play a vital role in surveillance applications, enhancing security measures by autonomously identifying and tracking multiple vehicles.
PLATE.VISION - License Plate Identifier by Makewise
The PLATE.VISION system - ANPR (Automatic Number Plate Recognition)? - is a real-time vehicle identification software (License Plate, Vehicle Identification Number, Brand and color, etc.).
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