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Introduction to Automatic Number Plate Recognition (ANPR)

It goes without saying that the boundaries of technology keep expanding daily. Over the years, we have seen useful equipment in various areas of technologies like IoT, Artificial Intelligence, Cybersecurity, and others. Well, in this case, Automatic Number Plate Recognition is an IOT solution—revolutionizing transportation and security services.

Table of Contents

What is Automatic Number Plate Recognition (ANPR)?

Automatic Number Plate Recognition is an IOT solution that uses computer vision technology to automatically scan vehicle number plates without human intervention. Anpr scans the number plates of vehicles in real-time and traces them in the database.

Ever watched those Sci-Fi/Action movies, where the police are chasing down the culprit of a crime scene? Oftentimes, they use the surveillance cameras on the road to scan the license plate number of the vehicle to find out who the owner is. Those cameras are examples of ANPR devices.

Additionally, ANPR goes by other names:

  1. Automatic Vehicle Identification(AVI)
  2. Car-Plate Recognition(CPR)
  3. Automated License Plate Recognition(ALPR)
  4. Vehicle recognition identification (VRI)
  5. License-plate recognition (LPR)
  6. Lecture automatique de plaques d’immatriculation (LAPI)

How does Automatic Number Plate Recognition (ANPR) Work?

From the name, you might think the ANPR process is complex, but it’s quite simple. ANPR uses optical character recognition(OCR) and image processing methods to collect and process the number plate of vehicles.

The images collected are processed using machine learning algorithms, but before then, there are several key steps:

  1. Image Capturing: ANPR uses special cameras equipped with infrared illuminators to capture the number plates of vehicles. Actually, infrared helps enhance the visibility of the characters on the plate.
  2. Pre-processing: After capturing the image, it has to undergo an editing phase to reduce noise and increase image quality. 
  3. Segmentation: This is when the image is broken down into different segments to analyze the image. It helps separate and identify each character on the number plate.
  4. Character Recognition: So, After segmentation, the license plate image is analyzed using optical character recognition(OCR) algorithms. It identifies and extracts the alphanumeric characters on the license plate.
  5. Character Verification: Oftentimes the data gotten from the license plate are compared against a database for security and accuracy. Additionally, if the data is false or comes out ambiguous, it undergoes further computational analyses or investigation.
  6. Data Integration and Storage: This is the final stage where the data analyzed is stored for future reference. Information collected from license plates of vehicles, along with their necessary metadata are stored. The metadata can be data, time, and location.

Benefits of Automatic Number Plate Recognition

Automatic Number Plate Recognition is making strides in various industries around the world. But what are the key benefits hidden in this technology? Let’s find out:

Traffic Management

As the world is transitioning into smart cities, ANPR is crucial in the management of traffic. It helps traffic control personnel understand the flow of traffic in certain areas of the city.

Additionally, we all know how real-time information about traffic situations can help us plan our route to work or any activity. ANPR cameras across the city can track the speed of individual vehicles and relay it to the traffic control center. This helps highlight the flow of traffic across the city and also for storing traffic information.

Also, besides tracking the traffic flow, ANPR can be used in the following ways:

  • Parking assistance
  • Pedestrian road crossing
  • Road congestion and road blockage detection
  • Road network planning

Law Enforcement

Various countries around the world deploy ANPR technology to ensure the laws set by their governments are upheld. Let’s take Australia for example, they were the first to deploy the fixed ANPR in 2005, on their various roads. After seeing its impact and usefulness, they did not waste time deploying mobile ANPR in 2009.

Why are countries so keen on having more ANPR technology? You might be wondering. Well, it helps track and trace stolen cars, people who violate traffic laws, speed control, track suspected terrorists, and many more.

When an ANPR camera picks up a suspected individual or activity, it sends an alarm to the authorities, and the necessary patrol units are dispatched.

Speed Control

Automatic number plate recognition is used to ensure the speed of drivers is not above the limit. It is configured to the speed laws of the country so that if a vehicle is driving at an illegal speed, it sounds an alarm to a patrol unit around the area.

Furthermore, this ANPR works by calculating the travel distance of the vehicle and finding the average speed. So, These ANPR cameras are called average-speed cameras.

Security Surveillance

The application of ANPR cameras for security purposes is extensive. From city junctions and parking grounds to toll collection points, it is used everywhere.

At toll booths, ANPR automatically detects the license plate of the vehicle and gives out the appropriate charge for that vehicle.

Also on parking grounds, it records the time every vehicle spends, to avoid an overcharge or undercharge.

Additionally, ANPR is used to track criminal activities in cities and alert the nearest police unit. By tracing the license plate, it becomes easier to catch and apprehend the culprit.

The above are some of the main uses of ANPR in our society, but there are other ways in which this technology is applied:

  • Border crossings
  • Drive-through Customer detection system: This automatically recommends certain items based on what the customer had bought before.
  • Hotel security
  • Analysis of travel patterns of vehicles
  • Marketing tool

Types of Automatic Number Plate Recognition (ANPR) Systems

Automatic Number Plate Recognition(ANPR) systems are constantly improving performance, reliability, and security across various sectors of the world. But what are the various types of ANPR that can be deployed? Let’s take a look:

  1. Fixed ANPR Systems

These systems are positioned at specific locations, around the city, parking grounds, border control posts, etc. They are used to monitor and capture the license plates of moving vehicles at constant intervals. Actually, the reason why fixed ANPR systems are widely used is because they can handle volumes of information. Meaning they can continuously monitor and capture the license plates of vehicles with high accuracy.

  1. Mobile ANPR Systems

Mobile ANPR systems are mainly used by patrol units. They are installed in their cars to detect the license plate of stolen cars or track down a criminal vehicle. 

Actually, these types of ANPR systems are designed to facilitate quick and accurate mobile surveillance. In fact, these systems are portable, flexible, and versatile when it comes to capturing the license plate of vehicles.

  1. AI ANPR Systems

It hasn’t been long since artificial intelligence took to the lips of everyone around the world and its application in various industries is numerous. In terms of ANPR systems, AI helps the automated process faster and better.

With machine learning models, ANPR systems can be trained on more accurate data to enhance their accuracy. 

Additionally, by integrating a cloud database, ANPR systems can easily access and analyze the licensed plates of vehicles faster.

How to Increase the Accuracy of Automatic Number Plate Recognition Systems

The task of increasing the accuracy of ANPR systems is no joke. Apart from it involving AI, it definitely needs data.

One significant way to increase the accuracy of ANPR systems is by training AI models on accurate data. Emphasis on ACCURATE!

Obviously, this task is not easy. Datasets are voluminous and need to be filtered for the AI model. When training the AI model, the objective is for it to accurately capture the image, read, examine, process, compare and interpret the information.

Although this task can be tough, once successful with the training of the AI model, it automatically carries out its task. However, the accuracy of the AI model will depend on the quality of the data used to train it.

Conclusion

Automatic Number Plate Recognition is one of the leading technologies around the world today. Its use to curb crime, enforce laws and ensure safety is what makes it in high demand. Additionally, with the advent of AI, ANPR is evolving daily. Finally, if you want to get your hands on this technology or you need to train your ANPR models, Macgence is just a click away.

Get Started with Macgence

Get started with Macgence, your ultimate destination for ANPR solutions. Our services encompass text, image, video, and AI model training, catering to all your machine learning and AI endeavors. Also, with Macgence, you’re assured of scalability, allowing us to handle projects of any size, and ensuring on-time delivery. We take pride in providing superior data quality, as our experts meticulously train your ANPR model to optimum performance. Our commitment to zero internal bias ensures fairness and neutrality, enhancing your AI systems’ integrity. Regardless of your industry, Macgence’s cross-industry compatibility ensures customized solutions tailored to your specific needs. So, Start today and experience the power of superior ANPR models at Macgence.

Frequently Asked Questions (FAQ’S)

Q1. What is Automatic Number Plate Recognition (ANPR)?

Automatic Number Plate Recognition is an IOT solution that uses computer vision technology to automatically scan vehicle number plates without human intervention. ANPR scans the number plates of vehicles in real-time and traces them in the database.

Q2. How does ANPR work?

ANPR utilizes optical character recognition (OCR) and sophisticated image processing techniques to gather and process license plate information. The process involves several key steps:

Image Capturing: Special cameras equipped with infrared illuminators capture license plate images, enhancing character visibility.

Pre-processing: Captured images undergo editing to reduce noise and enhance image quality.

Segmentation: Images are broken down into segments to analyze each character on the license plate.

Character Recognition: Optical character recognition algorithms analyze and extract alphanumeric characters from the segmented license plate image.

Character Verification: Extracted data may be cross-referenced with a database for security and accuracy, undergoing further analysis if needed.

Data Integration and Storage: Analyzed data, along with metadata such as date, time, and location, is stored for future reference.

Q3. What are the types of ANPR systems?

ANPR systems come in different types:

Fixed ANPR Systems: Positioned at specific locations, these systems continuously capture license plate data and are often used for traffic monitoring, parking, and border control.

Mobile ANPR Systems: Installed in patrol vehicles, these portable systems help track stolen vehicles and assist law enforcement in real-time surveillance.

AI ANPR Systems: Integrating artificial intelligence, these systems enhance accuracy by training on accurate data and accessing cloud databases for efficient analysis.

The post Introduction to Automatic Number Plate Recognition (ANPR) appeared first on Macgence.



This post first appeared on Data Processing For Machine Learning & AI, please read the originial post: here

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Introduction to Automatic Number Plate Recognition (ANPR)

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