Science Fair Project Encyclopedia
Automatic number plate recognition
Automatic number plate recognition (ANPR) is a mass surveillance method that uses optical character recognition on images to read the licence plates on vehicles. As of 2005 systems can scan number plates at around one per second on cars travelling up to 100 mph (160 km/h). They can either use existing closed-circuit television or road-rule enforcement cameras, or ones specifically designed for the task. They are implemented by various police forces and as a method of electronic toll collection on pay-per-use roads.
ANPR can be used to store the images captured by the cameras as well as the text from the licence 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 day. They also tend to be country-specific due to the variation of plates internationally.
The software aspect of the system runs on standard PC hardware and can be linked to other applications or databases. It first uses a series of image manipulation techniques to detect, normalize and enhance the image of the number plate, and finally optical character recognition to extract the alphanumerics of the licence plate. Typically, large numbers of PCs are used in a server farm to handle high workloads, such as those found in the London Congestion Charge project.
Media reports of misidentification and high error rates have led to privacy fears, though, as the systems have developed, they have become much more accurate and reliable.
ANPR is sometimes known by various other terms:
- Automatic vehicle identification (AVI)
- Car plate recognition (CPR)
- Licence plate recognition (LPR)
ANPR uses optical character recognition (OCR) on images taken by cameras. When Dutch Vehicle Registration Plates switched to a different style in 2002 one of the changes made was to the font, introducing small gaps in some letters (such as P and R) to make them more distinct and therefore more legible to such systems. Some licence plate arrangements use variations in font sizes and positioning – ANPR systems must be able to cope with such differences in order to be truly effective. More complicated systems can cope with international variants, though many programs are individually tailored to each country.
The cameras used can include existing road-rule enforcement or closed-circuit television cameras as well as mobile units which are usually attached to vehicles. Some systems use infrared cameras to take a clearer image of the plates.
There are five primary algorithms that the software requires for identifying a licence plate:
- Plate localisation – responsible for finding and isolating the plate on the picture
- Plate orientation and sizing – compensates for the skew of the plate and adjusts the dimensions to the required size
- Normalisation – adjusts the brightness and contrast of the image
- Character segmentation – finds the individual characters on the plates
- Optical character recognition
The complexity of each of these subsections of the program determines the accuracy of the system. During the third phase (normalisation) some systems use edge detection techniques to increase the picture difference between the letters and the plate backing. A median filter may also be used to reduce the visual "noise" on the image.
There are a number of possible difficulties that the software must be able to cope with. These include:
- Poor image resolution, usually because the plate is too far away but sometimes resulting from the use of a low-quality camera.
- Blurry images, particularly motion blur and most likely on mobile units
- Poor lighting and low contrast due to overexposure, reflection or shadows
- An object obscuring (part of) the plate, quite often a tow bar, or dirt on the plate
- A different font, popular for vanity plates (some countries ban such plates, eliminating the issue)
- Circumvention techniques
While some of these problems can be corrected within the software it is primarily left to the hardware side of the system to work out solutions to these difficulties. Increasing the height of the camera may avoid problems with objects (such as other vehicles) obscuring the plate, but introduces and increases other problems such as the adjusting for the increased skew of the plate.
Many countries now use licence plates that are retroreflective . This returns the light back to the source and thus improves the contrast of the image. In some countries, the characters on the plate are not reflective, giving a high level of contrast with the reflective background in any lighting conditions. A camera that makes use of infrared imaging (with a normal colour filter over the lens and an infrared light-source next to it) benefits greatly from this as the infrared waves are reflected back from the plate. This is only possible on dedicated ANPR cameras, however, and so cameras used for other purposes must rely more heavily on the software capabilities. Further, when a full-colour image is required as well as use of the ANPR-retrieved details it is necessary to have one infrared-enabled camera and one normal (colour) camera working together.
To avoid blurring it is ideal to have the shutter speed of a dedicated camera set to 1/1000th of a second. Because the car is moving, slower speeds could result in an image which is too blurred to read using the OCR software, especially if the camera is much higher up than the vehicle. In slow-moving traffic, or when the camera is at a lower level and the vehicle is at an angle approaching the camera, the shutter speed does not need to be so fast. Shutter speeds of 1/500 can cope with traffic moving up to 40 mph (64 km/h) and 1/250 up to 5 mph (8 km/h). 
Some small-scale systems allow for some errors in the licence plate. When used for giving specific vehicles access to a barriered area the decision may be made to have an acceptable error rate of one character. This is because the likelihood of an unauthorised car having such a similar licence plate is seen as quite small. However, this level of inaccuracy would not be acceptable in most applications of an ANPR system.
Vehicle owners have used a variety of techniques in an attempt to evade ANPR systems and road-rule enforcement cameras in general. One method increases the reflective properties of the lettering and makes it more likely that the system will be unable to locate the plate or produce a high enough level of contrast to be able to read it. This is typically done by using a plate cover or a spray, though the claims of the effectiveness of the latter are disputed. The covers are illegal and covered under existing laws, while in most countries there is no law to disallow the use of the sprays. 
Novelty frames around Texas licence plates were made illegal on 1 September 2003 by Senate Bill 439 because they caused problems with ANPR devices. That law made it a Class C misdemeanour (punishable by a fine of up to US$200), or Class B (punishable by a fine of up to US$2,000 and 180 days in jail) if it can be proven that the owner did it to deliberately obscure their plates. 
If an ANPR system cannot read the plate it can flag the image for attention, with the human operators looking to see if they are able to identify the alphanumerics. It is then possible to do lookups on a database using wildcard characters for any part of the plate obscured, and use car details (make and model, for example) to refine the search.
After the licence plate has been identified it can then be cross-referenced against a police database. The primary objectives of this are to identify vehicles that have been stolen, used in a crime or are in violation of some other law. Some systems are also linked to insurance databases to monitor if the vehicle is currently insured.
Project Laser in the United Kingdom
This followed a series of trials that commenced in 2002 when the Vehicle and Operator Services Agency (VOSA) was given funding by the Home Office to work with the Police Standards Unit and develop "Project Laser". With the aim of running the ANPR system nationwide, it was initially trialled by nine police forces and ran between 30 September 2002 and March 2003. Those police forces were:
- Greater Manchester
- North Wales
- Avon and Somerset
- The Metropolitan Police Service
- West Yorkshire
- West Midlands.
The second phase of the project ran between 1 June 2003 and 21 June 2004 and involved 23 police forces in total. The DVLA is also involved with Project Laser, using the system to gather details on unregistered and unlicenced vehicles and those without a valid MOT certificate or insurance cover.
"Eventually the database will link to most CCTV systems in town centres, meaning that all vehicles filmed on one of the many cameras protecting Bedford High Street, for instance, can be checked against the database and the movements of wanted cars traced to help with serious crime investigations."The project was seen as a success despite a Home Office report showing that the Driver and Vehicle Licensing Agency (DVLA) trial had an error rate of up to 40%, with claims that the system was contributing
— Bedfordshire Police
"…in excess of 100 arrests per officer per year – ten times the national average…"
—Police Standards Unit.
Further findings went on to show that the error rate dropped to 5% when infrared systems and updated software were used.
During the second phase of the project around 28 million number plates were spotted in total, with 1.1 million (3.9%) of these matching an entry in one of the databases. 180,543 vehicles were stopped (101,775 directly because of the ANPR system), leading to 13,499 arrests (7.5% of the total) and the issue of 50,910 fines (28.2%). 1,152 stolen vehicles (worth £7.5 million in total), £380,000 worth of drugs and £640,000 worth of stolen goods were also recovered. The primary goal of the second phase was, however, to see how well the costs of the ANPR system could be covered. The final conclusion was that less than 10% of the expenditure incurred was recouped, with the Home Office claiming that the failure of drivers to pay fines contributed to this low figure, and continued to recommend the system be deployed throughout the UK. Report (PDF)
Many cities and districts have developed traffic control systems to help monitor the movement and flow of vehicles around the road network. This had typically involved looking at historical data, estimates, observations and statistics such as:
- Car park usage
- Pedestrian crossing usage
- Number of vehicles along a road
- Areas of low and high congestion
- Frequency, location and cause of road works
CCTV cameras can be used to help traffic control centres by giving them live data, allowing for traffic management decisions to be made in real-time. By using ANPR on this footage it is possible to monitor the travel of individual vehicles, automatically providing information about the speed and flow of various routes. These details can highlight problem areas as and when they occur and helps the centre to make informed incident management decisions.
Some counties of the United Kingdom have worked with Siemens Traffic  to develop traffic monitoring systems for their own control centres and for the public. Projects such as Hampshire County Council's ROMANSE provide an interactive and real-time web site showing details about traffic in the city. The site shows information about car parks, ongoing road works, special events and footage taken from CCTV cameras. ANPR systems can be used to provide average driving times along particular routes, giving drivers the ability to choose which one to take. ROMANSE also allows travellers to see the current situation using a mobile device with an Internet connection (such as WAP, GPRS or 3G), thus allowing them to be alerted to any problems that are ahead.
Electronic toll collection
Ontario's 407 ETR highway uses a combination of ANPR and radio transponders to toll vehicles entering and exiting the road. Radio antennas are located at each junction and detect the transponders, logging the unique identity of each vehicle in much the same way as the ANPR system does. Without ANPR as a second system it would not be possible to monitor all the traffic. Drivers that opt to rent a transponder for C$2.00 per month are not charged the "Video Toll Charge" of C$3.45 for using the road, with heavy vehicles (those with a gross weight of over 5,000 kg) being required to use one. Using either system, users of the highway are notified of the usage charges by post. 
Charge zones – the London Congestion Charge
The London Congestion Charge is an example of a system that charges motorists entering a payment area. Transport for London (TfL) uses ANPR systems and charges motorists a daily fee of £5 (payed befor 10pm) if they enter, leave or move around within the London Congestion Charge zone between 7 a.m. and 6:30 p.m., Monday to Friday.
Two hundred and thirty CCTV-style cameras, of which 180 are installed at the edge of the zone, are currently in use. In addition to the 180 cameras on the edge of the zone, there are fifty further cameras placed within it. These cameras are intended to pick up cars that are missed on entry and/or exit and those that are moving solely within the zone. There are also a number of mobile camera units which may be deployed anywhere in the zone.
It is estimated that around 98% of vehicles moving within the zone are caught on camera. The video streams are transmitted to a data centre located in Central London where the ANPR software deduces the registration plate of the vehicle. A second data centre provides a backup location for image data.
Both front and back number plates are being captured, on vehicles going both in and out – this gives up to four chances to capture the number plates of a vehicle entering and exiting the zone. This list is then compared with a list of cars whose owners/operators have paid to enter the zone – those that have not paid are fined. The registered owner of such a vehicle is looked up in a database provided by the DVLA. 
The introduction of ANPR systems has led to fears of misidentification and the furthering of 1984-style surveillance. In the United States, some such as Gregg Easterbrook oppose what they call "machines that issue speeding tickets and red-light tickets" as the beginning of a slippery slope towards an automated justice system:
- "A machine classifies a person as an offender, and you can't confront your accuser because there is no accuser... can it be wise to establish a principle that when a machine says you did something illegal, you are presumed guilty?"
Similar criticisms have been raised in other countries. Easterbrook also argues that this technology is employed to maximize revenue for the state, rather than to promote safety.
Systems are still fallible with one critic of the London Congestion Charge scheme noting "Misread plate after misread plate appeared on the screen – of every 10 that appeared at least four were incorrect."  This can lead to charges being made incorrectly with the vehicle owner having to pay £10 in order to be issued with proof (or not) of the offence.
Other concerns include the storage of information that could be used to identify people and store details about their driving habits and daily life, contravening the Data Protection Act 1984 along with the freedom of information and similar legislation. The laws in the UK are strict for any system that uses CCTV footage and can identify individuals. 
ANPR systems may also be used by:
- Border crossings
- Filling stations to log when a driver drives away without paying
- Car parks or road entry systems to control access
- A marketing tool to log patterns of use
- Traffic management systems, which determine traffic flow using the time it takes vehicles to pass two ANPR sites
- "ANPR". Police Information Technology Organisation (PITO). Accessed 28 March 2005.
- "Automatic Number Plate Recognition (ANPR)". Police Standards Unit, PoliceReform.gov.uk. Accessed 28 March 2005.
- "Business plan" Driver and Vehicle Licensing Agency, 10 June 2004. Accessed 28 March 2005.
- "Driving crime down". Home Office, October 2004. Accessed 29 March 2005.
- "Operation Mermaid – National ANPR Day". Bedfordshire Police, 19 May 2003. Accessed 28 March 2005.
- "What is a transponder", 407 ETR. Accessed 31 March 2005.
- Constant, Mike. "CCTV Information – ANPR". Accessed 30 March 2005.
- Hofman, Yoram. "License Plate Recognition - A Tutorial". Accessed 28 March 2005.
- Sexton, Steve. "License-plate spray foils traffic cameras". Accessed 5 April 2005.
- Lettice, John. "The London charge zone, the DP Act, and MS .NET". The Register, 21 February 2003. Accessed 28 March 2005.
- Lettice, John. "No hiding place? UK number plate cameras go national". The Register, 24 March 2005. Accessed 28 March 2005.
- Millar, Chris. "Exposed: Ken's camera spies". ThisIsLondon.com , 20 February 2003. Accessed 28 March, 2005.
- Siemens Traffic, "Recognising a new way to keep traffic moving". Accessed 3 April 2005.
- Wentworth, Jeff , "Obscured license plate could be motorists' ticket to fine". Accessed 5 April 2005.
Companies and agencies using and providing ANPR systems:
- Vehicle and Operator Services Agency (VOSA)
- Police Information Technology Organisation (PITO)
- 407 ETR
- Transport for London
- ROMANSE – Traffic and Travel Information for Hampshire, Portsmouth and Southampton
News and reports:
- "Number plate recognition poised for national UK rollout" at The Register
- "Number plate scan to be extended" at BBC News
- "No Smiles for the Camera" at SourceUK.net
- "London Congestion Charge CCTV privacy concerns" at spy.org.uk
- Other privacy issues at Privacy International
- "Car Cloning" at BBC Inside Out
- Plate Recognition at PhotoCop.com
- "A Real-time vehicle License Plate Recognition (LPR)" at visl.technion.ac.il
- "An Approach To Licence Plate Recognition" – a PDF file describing a University of Calgary project that looks at plate location in raster images
Information from developers of ANPR systems:
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