Automated Number Plate Recognition (ANPR) software application uses optical character recognition (OCR) on images. The technology reads vehicle license plates, and the application automatically identifies the vehicle. ANPR applies to law enforcement, vehicle tracking, and electronic toll collection.
Applications of Automatic Number Plate Recognition
- ANPR applies to the police force and law enforcement as it helps them confirm vehicle registration and licensing.
- The system is a method of cataloging traffic movement and monitoring traffic offenders.
- With ANPR, it’s easier to detect a traffic incident or accident and respond effectively.
- ANPR is also used in electronic toll collection on pay-per-use roads.
There are several types of automation tools for license plate recognition:
Portable
The portable kinds of tools are mostly installed on traffic trailers. And from their name, they are easily moved from one location to another. The system uses Wi-Fi connections with the aid of air cards. In addition, they charge and run with the help of solar energy.
Fixed
The fixed automation set-up consists of at least four permanently installed C3 series cameras coupled with a color overview and infrared technology. The cameras can read multiple traffic lanes simultaneously and capture plates from different vehicles. ANPR software works under all weather conditions, day or night, even when the vehicle moves at a maximum speed of 130mph.
Mobile
Mobile automation is installed for protection and surveillance. Hence common in the special Operation department as a form of intelligence and security services.
The cameras can scan a maximum of 100 vehicle plates per second. In addition, mobile automation works from every angle and under any weather condition.
How Automatic Number Plate Recognition Software Application Works
Most ANPR systems utilize several techniques. They include the following:
Image Pre-selection and ANPR
The software will try to derive the plate number and trace the plate type from the image taken. ANPR utilizes image enhancement and image normalization to identify the vehicle and magnify the plate on the captured image.
Optical Character Recognition (OCR) is essential as its algorithm identifies the individual character and translates them into digital text data.  Â
Vehicle Detection and Image Capture
The ANPR system has a camera at the front end, enabling it to capture images of vehicles and license plates. ANPR results depend highly on cameras as a captured image improves the system’s overall performance. In addition, ANPR cameras have specialized features to get the job done.
ANPR Data Recording and End-User Application
Besides recognition of the type of vehicle plate and individual characters, ANPR also offers additional information. Such as:
- The nationality and color of the plate with time stamps and geographical coordinates.
- It increases the confidence level of the characters and the whole plate.
- Images with recognizable plates.
Real-time Object Detection
Object detection lets the software recognize the vehicle in real time, whether it’s a bus, motorcycle, van, truck, or car. Object detection algorithms like Yolov3 or Yolov7 utilize neural networks trained on a dataset of images.
Optical Character Recognition
OCR is a vital computer vision tool in the ANPR system as it reads texts in images. OCR makes it possible for ANPR to identify license plates. Other techniques are, MaskOCR and Tesseract OCR which detect the characters, identify their sequence and translate the number plate image into text.
Template Matching
Template matching is when the taken image is compared to other images of license plates. The image is run through a library of images in search of a match. Template matching uses a specific pattern to identify the text or characters in vehicle number plates.
Image Processing
The images taken in real-time environments may be unclear. Factors like weather, dust, illumination, occlusion, and inconsistent set-ups influence the outcome of the images. Image processing helps prepare the images for processing by the OCR algorithm. Image processing sharpens the focus, corrects color, and crops the insignificant part of the pictures. In addition, it improves the results and output of the ANPR software.
Benefits of Automatic Number Plate Recognition Software
ANPR is valuable software with numerous benefits in different applications. The software’s accuracy depends on its performance, and the quality of the input received. Below are several advantages of ANPR:
Accuracy
The ANPR systems are highly accurate and can identify different vehicles by their license plates in no time.
Automation
The ANPR technology is automated, and the collected data is displayed on screens. The technology is ideal for monitoring small cities and toll stations. In addition, it offers automated alerts and controls for facilities.
Analytics
The collected data is helpful in traffic flow analytics. The ANPR has several uses in the Intelligent Transport System (ITS). They include the following:
- Reducing traffic congestion
- Managing accidents and incidents effectively
- Improving the mobility of people and goods
- Increase safety
Versatility
Apart from monitoring traffic, the ANPR is applicable in parking management, logistics optimization in manufacturing, and traffic and security enforcement, among others.
Security
ANPR offers surveillance features that play a part in security. The systems provide you with images, which can help identify a particular vehicle making tracking easier.
Deterrent
The presence of automation tools is enough to discourage traffic offenders. People tend to act right as the thought of being watched is at the back of their minds. It’s hard to get past the system, especially for criminals who may have gotten away on different occasions or those with misdemeanors.
Bottom Line
ANPR technology utilizes optical character recognition to read images of vehicle license plates. The tool benefits road and traffic enforcement as it makes it easier to monitor the roads. However, the ANPR has raised privacy concerns and is described as a form of mass surveillance.