Automatic License Plate Recognition (ALPR): What it is and How it Works

automatic license plate recognition
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Even the presence of a camera may be enough to make unscrupulous individuals abandon any nefarious ideas or plans. Fortunately, these devices can also be helpful in more powerful ways.

A survey of 422 incarcerated burglars revealed security cameras as the most effective deterrent to theft. 60% of the surveyed offenders said they would choose a different site if their target location had security cameras.

More than 70% of crimes in the US involve a vehicle, and license plates are public information. An Automated license plate recognition (ALPR) system can significantly aid the authorities in holding criminals accountable and meting out justice.

In addition to controlling crime, ALPR technology has many other uses. This article will explore what ALPR is and how it works. We will also discuss its benefits and well-known applications.

What is the ALPR System?

The automated process that identifies a vehicle by photographing its license plate and scanning it is known as license plate recognition (LPR). Automated license plate recognition (ALPR) comprises high-speed and computer-controlled camera systems.

They deploy industry 4.0 solutions such as computer vision technology that can read plates exponentially faster than cameras or human operators. ALPR systems are used for traffic enforcement, threat detection, traffic control, access control, toll collection, parking management, and more.

ALPRs are sensor-based video analytics. They automatically capture any license plate number within their line of sight. These pictures are also time, date, and location stamped. ALPR cameras can either be mobile or stationary.

ALPRs scan the license plates on vehicles. This information is uploaded to a central server and can be accessed by authorized personnel with proper login credentials.

In the next section, we will explore how an ALPR system operates.

How Does ALPR Work?

ALPR can scan the plate on any registered vehicle. Analytic software then classifies the number plates according to code. This data can be used for locating a car on a digital map, parking control, toll collection, traffic management, and security and surveillance.

The camera is a vital component of an ALPR system. It captures the license plate number of a vehicle and can either be stationary or mounted on another vehicle. ALPR cameras can also record short videos of passing vehicles. These videos can be uploaded to a central server and viewed later.

All ALPR data that is recorded by the cameras is public information.

Stationary ALPR cameras are located at fixed places and cover a particular roadway area. A single-camera ALPR system may need to be more efficient to capture all the vehicles passing through a site. Multi-camera ALPR systems operating simultaneously can deliver significantly higher success rates.

Mobile ALPR cameras are attached to vehicles and can capture license plate numbers complete with date and time stamps. These cameras are designed to function at night and under all weather conditions. They have multi-purpose applications, including retrieving lost or stolen license plates, locating stolen vehicles, crime control, highway and traffic management, and more.

The analytic software translates videos and still images into machine-readable characters. ML models, such as the ones driving license plate detection technology, require large amounts of data. Model training helps ALPR systems generate vast amounts of data, and optical character recognition (OCR) algorithms facilitate ALPR solutions.

OCR leverages a quality image repository that allows its algorithms to match images to each other. The algorithm can complete operations exponentially faster than human operators using software that can process blurred images, multiple rows, and specific colors and fonts.

OCR technology uses the following six algorithms to deliver high-accuracy output.

Image Acquisition

Image recognition and license plate image capture are different from each other. The computer vision technique recognizes an image captured by a camera. It is the method of identifying objects in a video or image frame through the automatic processing of videos or still photos.

Computer vision tools follow predefined rules to spot objects and patterns in a vehicle image. It can also identify multiple license plates within an image comprising several vehicles.

ALPR companies commonly use tech stacks like OpenCV Library and Python to train machine learning algorithms to recognize license plates.

Image Localization

For every frame in a video, a mathematical formula or a localizing function determines what a particular area in an image represents. The direction in which the vehicle is traveling and the distance from the camera and the angle are used to gauge if the vehicle is moving or stationary.

Rectangular-shaped license plates are easier to spot. However, there may be multiple rectangular-shaped objects on the vehicle. The algorithm uses unique features to distinguish a license plate from other objects on the vehicle.

Sizing, Orientation, and Normalization

Image distortion poses a challenge to LPR algorithms. The algorithm regulates the brightness and contrast of the captured license plate image while flagging several vehicles from multiple angles simultaneously. A usable image should possess the optimal size and correct proportions.

These parameters are controlled by thresholds.

The image of a stationary car is less complex than one in motion. Furthermore, the ambient light conditions of night-time and daytime and the weather directly generate blurry photos. Fortunately, customized and advanced ALPR software can help address all these pain points.

Character Segmentation

Character segmentation helps in detecting the different kinds of constituent parts. The algorithm breaks the license plate image into fragments. Individual numbers and letters are isolated using parameters such as structure, font, and distance between characters and color.


The captured image can be translated into an alphanumeric text at this stage. The algorithm will match this text to the list of numbers stored in the database.

Geometrical and Syntactical Analysis

The algorithm can analyze individual numbers or letters and assign each class. How complicated the captured license plate is will determine the criteria that govern these classes.

The aforementioned stages help users extract value from an ALPR application, enabling them to meet their business objectives.

What are the Benefits of Using ALPR?

The following are some of the key benefits of using ALPR technology.


Whether it’s an active emergency, a police investigation, or a high-speed chase, every second counts. The faster you can extract and process critical information, the better.

In addition to reading vehicle plates, ALPRs can run them against databases in real-time to accelerate identity verification. Even in heavy traffic, these systems can flag vehicles of interest within seconds.

Some ALPR systems also offer time and date stamps and information about where the vehicle was last spotted by the centralized ALPR setup.

In metered parking environments where motorists are tagged by their number plates instead of parking space, ALPRs can help cross-reference plates with parking time expired or remaining, facilitating the proper enforcement of local regulations.


Accuracy plays a vital role in public safety and law enforcement. Errors can lead to wasting precious resources that could otherwise be utilized to serve and protect the community.

ALPR systems can reduce uncertainty in traffic patrolling. It can help to identify any motorist or vehicle quickly.

The job of traffic police is complex and challenging. Factors like the time of day or traffic density can hinder their ability to identify vehicles or persons accurately. ALPR systems can fill in the gaps the human eye has missed.

ALPR systems can accurately photograph vehicle license plates even in moving traffic. It can capture high-resolution images at great distances, even on high-volume and high-speed roadways.

Leveraging infrared and color sensors, some ALPR systems can capture vivid shots at more than 30 frames per second. This includes environments and times of the day that offer poor light conditions.


ALPRs are an invaluable resource for cross-referencing data and automating license plate detection. It can save precious energy and time and deliver high accuracy. In the time it takes to process up to 100 plates manually, an ALPR system can process 5000 or more.

ALPR automation frees up time for professionals, allowing them to attend to tasks impossible without human intervention. Users receive real-time updates through notifications.


ALPRs can help the authorities apprehend the perpetrators more quickly, especially in burglaries, runaway suspects, and car thefts. These systems can also help catch culpable individuals before they can flee the crime scene.

Authorities can seamlessly integrate critical tools like historical vehicle location data, associate analysis, and predictive analytics to generate fast and reliable leads.


Automation significantly reduces the investments it takes to run a manual security system. Additionally, the substantial increase in efficiency and accuracy resulting from automation leads to further cost savings.

For example, the mere installation of ALPR cameras reduces petty crimes like theft, trespassing, vandalism, and illegal dumping, saving considerable amounts in clean-up costs alone.

Increase Revenue

Parking lots that deploy 24/7 ALPR systems to monitor access, automatically issue tickets for illegal activities caught on camera, and optimize drive-through times have experienced an uptick in revenue.

Ease of Installation

ALPRs can be set up even in remote locations that do not offer conventional internet access. These systems run on solar power and use wi-fi to patrol remote areas.

Irrefutable Evidence

High-quality videos, images, and verified license plates can prove violations beyond any reasonable doubt. ALPRs can also store information such as the model, make, and color of vehicles for future use.

In the next section, we will explore two well-known use cases of ALPR technology.

Use Cases of ALPR

Apart from law enforcement and traffic management, the following are two other well-known use cases of ALPR.

Drive-Thru Management

Americans visit drive-thrus 6 Bn times each year. Since they offer the customer a contactless and socially distanced experience, the pandemic saw a 25-35% increase in drive-thru sales.

Kevin Johnson, the CEO of Starbucks, noted that the drive-thru generated more than 50% of their net sales in Q2 of 2021.

At 97%, South Korea enjoys the highest smartphone penetration in the world. It is also the 2nd largest global market for Starbucks by store count. In 2018, Starbucks Korea launched its ALPR service, known as My DT Pass Service. It allowed customers to automate their coffee purchase payments by linking the number plates of their cars to the coffee chain’s pre-paid cards.

The application reduced the total wait time by 10%, shortening 13-15 seconds per car in the drive-through lane. 40% of Starbucks Korea drive-thru customers were availing the ALPR service in 2020.

In Oct 2020, the company reported 1.5 Mn My DT Pass users in Korea, a 50% increase from 1 Mn only eight months back and averaging 6000 registered users across its 268 drive-thru outlets.

In 2020, the average check size in quick-service restaurants was $10.99. ALPR technology can help drive-thrus process up to 30 more cars daily. At these rates, the potential increase in annual sales per store would be around $132,000.

Auto Service Experiences

In service environments like a carwash, an auto dealership service lane, or a gas station, license plate detection can help improve lifetime value, productivity, and customer loyalty.

When drivers arrive at the service lane in their cars, a personalized welcome note greets them on a video screen. Regular customers can automate their payments without producing their credit cards each time.

Every time a regular customer arrives, service managers are alerted with a history of the customer’s past requirements, enabling them to serve the customers better.

In Apr 2021, the parent company of Circle-K announced that, after successful trials, it would be installing ALPR-based solutions in gas stations across multiple countries. The company noted that this roll-out would be the first in the market.

Combining a mobile app and ALPR would offer a better fueling experience to customers. Number plate recognition would enable customers to fill up and pay on the company’s Easy Fuel app. Customers need not provide a card or pin for each transaction.


At Gramener, we offer cutting-edge ALPR solutions to help you transform your business operations, enhance security and elevate the customer experience.

If you want to implement ALPR applications at your organization, connect with us today.

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