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ANPR automatic license plate recognition technology

From fine cameras to non-stop toll collection - it all starts with ANPR. Automatic license plate recognition technology is quietly operating behind thousands of cameras across Vietnam, helping to record violations, optimize traffic flow and improve vehicle management efficiency. But did you know that behind this system is an extremely complex AI and data processing network? So how does ANPR work? Let's explore with KPS in the article below!

What is ANPR? How does it work?

What is ANPR?

ANPR (Automatic Number Plate Recognition) or Automatic License Plate Recognition Technology, a system that uses specialized cameras combined with artificial intelligence (AI) to automatically detect, capture and analyze license plate images, allowing computers to read license plate images from images captured by cameras. This technology converts optical information on the license plate into text data, thereby creating vehicle location data.

The core role of ANPR lies in its monitoring and management capabilities. By integrating identified license plate data with vehicle registration databases, the system can quickly identify details about the owner, registration location, and compliance status (such as checking for stolen or infringed vehicles).

How ANPR systems work

ANPR technology operates based on a combination of specialized cameras, image processing using artificial intelligence (AI) and optical character recognition (OCR) algorithms. The entire process is performed completely automatically - real-time in just a few thousandths of a second, ensuring high accuracy even in complex conditions such as low light, dirty license plates or high-speed vehicles.

Step 1: Image collection stage

The main equipment is ANPR cameras installed at strategic locations such as toll booths, control gates, parking lots, or intersections. These cameras have high resolution and use infrared (IR) light to capture clear license plate images in all conditions - day, night, or bad weather. Some systems also integrate polarizing filters to eliminate glare and reflections from metal surfaces or vehicle headlights.

Step 2: Image Pre-Processing: This is the stage of filtering noise and improving image quality to increase accuracy when recognizing characters. Processing steps include:

  • Converting color images to grayscale images.
  • Increasing contrast, balancing light and dark.
  • Noise Filtering using Gaussian or Median Filter algorithms.
  • Determining the area containing the license plate (Plate Localization) through AI Object Detection.

Step 3: Plate Detection

  • Using traditional methods:
    • Edge Detection - finding rectangles.
    • Segment by color, if the license plate has a characteristic background color.
  • Or use AI/Deep Learning:
    • CNN, YOLO, or SSD networks to directly identify the license plate location.
    • Advantages: accurate, independent of color or lighting environment.

» Then filter the results, remove fake areas, only keep the most suspicious area with rectangular shape, standard ratio of the license plate.

Step 4: Extract the license plate:

  • Preprocess the license plate area:
    • Convert the license plate area to a binary image (black & white) so that the characters stand out more from the background.
    • Enhance the contrast and sharpen the characters, ensuring clear details of numbers/letters.
  • Character Segmentation:
    • Separate characters using contour detection, connected component analysis or projection profile.
    • With AI systems, CNN/CRNN models can segment characters automatically, which is especially useful when characters are tilted, obscured, or connected together.
  • Character Recognition (OCR):
    • Using an OCR model or a specialized neural network for license plates to recognize characters.
    • Can combine valid format checks according to license plate regulations to eliminate recognition errors.
  • Matching and validating results:
    • The recognized characters are matched in order to form a complete license plate.
    • Check the format, remove incorrect characters, and ensure high accuracy.

Step 5: Database Query

The recognized license plate data will be integrated with related databases (registered vehicle list, blacklist, violation information). This process allows the system to identify details about the vehicle, owner, address, and provide information necessary for applications such as access control or law enforcement.

Core technologies in modern ANPR

A modern ANPR system not only relies on camera hardware, but also on a sophisticated combination of AI, Computer Vision, Machine Learning, and Edge Computing. These core technologies help the system operate accurately, quickly, and stably in many real-life conditions.

  • Artificial Intelligence (AI) & Machine Learning: helps the system learn from millions of images, accurately recognize characters in many different conditions, achieving an accuracy of over 98%.
  • Computer Vision: helps analyze images, locate and recognize license plates, and detect traffic violations.
  • Advanced image processing: helps enhance image quality, remove noise, and correct shooting angles to ensure clear license plate characters.
  • Edge Computing: Process data directly on the camera, helping to reduce latency and increase response speed in real time.
  • Cloud Computing: Store, analyze and synchronize license plate data on a large scale, support centralized monitoring and management.
  • Security & compliance with international standards: Data encryption, access authentication and compliance with NDAA, FIPS 140-2 standards to ensure information security

Practical applications of ANPR

ANPR technology has become an indispensable tool, helping to improve traffic management efficiency, security and minimize human intervention in operational processes.

Applications in Intelligent Transportation Systems (ITS)

Traffic violation monitoring

  • ANPR helps detect violations such as speeding, running red lights even when the vehicle is moving at high speed.
  • Violation data is automatically recorded and integrated into the processing system, helping to increase the effectiveness of law enforcement and road security.

Automatic Road Toll Collection (ETC/Tolling)

  • The ANPR system automatically captures and recognizes license plates when a vehicle passes through a toll booth or speed monitoring camera.
  • The license plate data is used to automatically send tickets or invoices, replacing manual toll collection.
  • This solution is especially effective in reducing congestion on highways, increasing traffic speed.

Travel time analysis

  • The system records the travel time from the starting point to the destination of the vehicle.
  • Provides important data for traffic flow analysis and signal control optimization, helping to effectively manage congestion in real time.

Security, Surveillance and Access Control

Smart Parking Management

  • Automate vehicle entry and exit processes, limit illegal parking.
  • Record images and vehicle information to collect detailed data for parking management.

Hybrid Access Control

  • ANPR combined with biometric identification to create a comprehensive access control system.
  • Suitable for factories, headquarters or areas requiring high security, easy management and reduced operating costs.

Restricted Area Security

  • The system is deployed in high security areas such as military facilities, testing areas or important government buildings.
  • Automatically recognizes and authenticates authorized vehicles, enhancing perimeter security.

Law Enforcement Support

  • The system records license plates, symbols, colors and vehicle characteristics.
  • This data supports law enforcement agencies in investigating, tracking and controlling vehicles according to regulations.

ANPR Development Trends in Vietnam

ANPR technology in Vietnam is growing strongly, focusing on smart traffic projects, technical upgrades with AI, and strict legal compliance.

Technical upgrades with Artificial Intelligence (AI) and Edge Computing

Improving accuracy with AI

  • Replacing traditional algorithms with Deep Learning models (YOLO, CNN) to recognize license plates in low light conditions, tilted or obscured license plates.
  • Recognition accuracy reaches 93 - 95%, much higher than traditional systems.

Optimizing Vietnam's license plates

  • Research and refine the model to recognize diverse license plate structures (cars, motorbikes, many types of characters).
  • OCR for digits reaches 99.5%, and the overall system aims for recognition efficiency of over 90% in real conditions.

Edge Computing

  • Integrate processing directly on the camera for instant decision making.
  • Reduce network latency and reduce bandwidth required for large-scale surveillance systems.

Focus on Intelligent Transportation Systems (ITS) and Automatic Toll Collection

Automated Toll Collection (ETC)

  • ANPR is the foundation technology for non-stop toll collection on highways and bridges.
  • The system automatically captures and recognizes license plates, generates invoices or tickets accordingly, helping to reduce congestion at traditional toll booths.

Traffic and Violation Management

  • ANPR is deployed at key intersections to monitor violations such as speeding, red light violations, and collect real-time vehicle data.

Smart Parking Management

  • Automate parking lot entry and exit processes and vehicle control.
  • Improve security, reduce illegal parking, and support vehicle data collection.

Legal Compliance and Privacy Protection

Sensitive Data

  • ANPR data (images, time, location) is considered Sensitive Personal Data.
  • The collection, storage and processing of data must comply with strict regulations to protect privacy.

The Personal Data Protection Act (PDP 2025)

  • Effective from 1 January 2026, requires ANPR deployment organizations to obtain explicit consent from vehicle owners and comply with data privacy regulations.

Information transparency

  • ANPR projects should clearly communicate the purpose, scope and manner of data processing.
  • Conduct a Privacy Impact Assessment before deploying the system to ensure compliance with the law and the rights of citizens.

KPS - A provider of security solutions and smart traffic monitoring in Vietnam

KPS is a pioneer in providing security solutions and smart traffic systems in Vietnam. With 15 years of experience implementing large-scale projects in key areas such as transportation, government, industry, smart buildings and urban infrastructure, KPS not only provides quality equipment but is also a strategic technology partner to help optimize operational efficiency and safety management.

As an official distributor of the world's leading surveillance brands such as i-PRO (Panasonic), BOSCH, CNB, KPS provides comprehensive solutions from design, technical consulting, system integration to long-term maintenance and operation.

KPS pays special attention to the application of artificial intelligence (AI), computer vision and edge computing in surveillance systems - helping to enhance license plate recognition, vehicle behavior analysis, traffic control and ensure smart urban security.

We have a team of specialized engineers and an international quality management process. With the operating philosophy of "Safety - Accuracy - Efficiency - Sustainability", KPS is committed to accompanying partners in building modern, reliable and smart traffic and security infrastructure in line with the national digital transformation trend.

Contact KPS for advice on comprehensive ANPR and smart traffic camera solutions.

Hotline: 0933 933 018

Email: info@kps.com.vn

KPS System Corp.


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Công ty cổ phần Hệ Thống An Ninh Khai Phát (gọi tắt là Công ty KPS). GPDKKD: 0310471658 do sở KH & ĐT TP.HCM cấp ngày 24/11/2010. Đại diện pháp luật: Đinh Tấn Đạt.

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