# What is Automatic Number Plate Recognition (ANPR)

February 13, 2018

With growing urban population and its supporting transport services, there is an urgent need to improve traffic management and secure the transport systems. Automation in transport has been used successfully in signaling systems and has helped in managing urban traffic to a great extent. Automatic recognition of vehicle license plate number became a very important in our daily life because of the unlimited increase of cars and transportation systems which make it impossible to be fully managed and monitored by humans, examples are so many like traffic monitoring, tracking stolen vehicle, managing parking toll, red-light violation enforcement, border and customs checkpoints.

### Automatic Number Plate Recognition: Overview

Automatic Number Plate Recognition (ANPR) system is an important technique, used in Intelligent Transportation System. ANPR is an advanced machine vision technology used to identify vehicles by their number plates without direct human intervention. The development of Intelligent Transportation System provides the data of vehicle numbers which can be used in follow up, analyses and monitoring. ANPR is important in the area of traffic problems, highway toll collection, borders and custom security, premises where high security is needed. The complexity of automatic number plate recognition work varies throughout the world. For the standard number plate, ANPR system is easier to read and recognize. In India this task becomes much difficult due to variation in plate model.

The Automatic number plate recognition (ANPR) is a mass surveillance method that uses optical character recognition on images to read the license plates on vehicles. They can use existing closed-circuit television or road-rule enforcement cameras, or ones specifically designed for the task. They are used by various police forces and as a method of electronic toll collection on pay-per-use roads and monitoring traffic activity, such as red light adherence in an intersection.

ANPR can be used to store the images captured by the cameras as well as the text from the license plate, with some configurable to store a photograph of the driver. Systems commonly use infrared lighting to allow the camera to take the picture at any time of the day. A powerful flash is included in at least one version of the intersection monitoring cameras, serving both to illuminate the picture and to make the offender aware of his or her mistake. ANPR technology tends to be region-specific, owing to plate variation from place to place.

### Automatic Number Plate Recognition: Definition

Automatic Number Plate Recognition (ANPR) technology is used to help detect, deter and disrupt criminality at a local, force, regional and national level. Automatic Number Plate Recognition (or as frequently called ‘License plate recognition’) is a special form of optical character recognition (OCR). License plate recognition (LPR) is a type of technology, mainly software that enables computer systems to read automatically the registration number (license number) of vehicles from digital pictures.

Automatic Number Plate Recognition (ANPR) is an image processing technology which uses number (license) plate to identify the vehicle. Automatic Number Plate Recognition (ANPR) is one such application that has become an essential commodity for managing traffic and enforcing rules. It can also be used effectively for security.

#### Figure 1: General ANPR System

ANPR systems are generally divided in four steps: (1) Vehicle image capture (2) Number plate detection (3) Character segmentation and (4) Character recognition.

As it is shown in Figure 1, the first step i.e. to capture image of vehicle looks very easy but it is quite exigent task as it is very difficult to capture image of moving vehicle in real time in such a manner that none of the component of vehicle especially the vehicle number plate should be missed. Presently number plate detection and recognition processing time is less than 50 ms in many systems. The success of fourth step depends on how second and third step are able to locate vehicle number plate and separate each character.

### Automatic Number Plate Recognition: Applications

Automatic Number Plate Recognition has a wide range of applications since the license number is the primary, most widely accepted, human readable, mandatory identifier of motor vehicles. ANPR provides automated access of the content of the number plate for computer systems managing databases and processing information of vehicle movements. Below we indicated some of the major applications, without the demand of completeness.

Law Enforcement: – The plate number is used to produce a violation fine on speeding vehicles, illegal use of bus lanes, and detection of stolen or wanted vehicles. License plate recognition technology has gained popularity in security and traffic applications as it is based on the fact that all vehicles have a license plate and there is no need to install any additional tracking apparatus. The main advantage is that the system can store the image record for future references. The rear part of the vehicle is extracted off the filmed image and is given to the system for processing. The processed result is fed into the database as input. The violators can pay the fine online and can be presented with the image of the car as a proof along with the speeding information.

Parking: – The LPR system is used to automatically enter pre-paid members and calculate parking fee for non-members (by comparing the exit and entry times). The car plate is recognized and stored and upon its exit the car plate is read again and the driver is charged for the duration of parking

Automatic Toll Gates: – Manual toll gates require the vehicle to stop and the driver to pay an appropriate tariff. In an automatic system the vehicle would no longer need to stop. As it passes the toll gate, it would be automatically classified in order to calculate the correct tariff.

Border Control: – Border Control is an established state-coordinated effort to achieve operational control of the country’s state border with the priority mission of supporting the homeland’s security against terrorism, illegal cross border traffic, smuggling and criminal activities. Efficient border control significantly decreases the rate of violent crime and increases the society’s security. Automatic number plate recognition adds significant value by event logging, establishing investigate-able databases of border crossings, alarming on suspicious passing, at many more.

Homeland Security: – The NPR system’s ability to read strings of alpha-numeric characters and compare them instantaneously to Hot Lists allows a Command Center to organize and strategize efforts in reaction to the information captured. Fixed NPR systems, which can be mounted to bridges, gates and other high traffic areas, can help keep a tight watch on entire cities, ports, borders and other vulnerable areas. Every NPR camera is capturing critical data such as color photos, date and time stamps, as well as GPS coordinates on every vehicle that passes or is passed. This incredible database provides a wealth of clues and proof, which can greatly aid Law Enforcement with

• Pattern recognition
• Placing a suspect at a scene
• Watch list development
• Identifying witnesses
• Possible visual clues revealed within the image of a car’s immediate environment

### References

[1] Chirag Patel and Dipti Shah, “Automatic Number Plate Recognition System (ANPR): A Survey”, International Journal of Computer Applications (IJCA), Volume 69– No.9, May 2013

[2] Priti Rajvanshi, “Automatic Number Plate Recognition- Approach for Detecting the Vehicle Number Plate On-The-Go”, Special Conference Issue: National Conference on Cloud Computing & Big Data, pp. 83-89

[3] M. M. Shidore and S. P. Narote, “Number Plate Recognition for Indian Vehicles”, IJCSNS International Journal of Computer Science and Network Security, Volume 11 Number 2, Feb. 2011

[4] Belal R. Mohamed and Hala M. Abd El Kader, “Automatic Number Plate Recognition”, International Journal of Scientific and Research Publications, Volume 3, Issue 12, December 2013.

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