This document provides an overview of automatic number plate recognition (ANPR) systems. It describes ANPR as a mass surveillance method that uses cameras and optical character recognition to read license plates on vehicles. The document outlines the history, components, technologies, algorithms, difficulties, and applications of ANPR systems. It explains that ANPR systems consist of cameras to capture images of license plates and software to recognize the characters and store the plate data.

1. AUTOMATIC NUMBER PLATE RECOGNITION
[ANPR]
CONTENTS
 INTRODUCTION
 ETYMOLOGY
 DEVELOPMENT HISTORY
 COMPONENTS
 TECHNOLOGY
 SYSTEM DESCRIPTION
* CAMERA
* SOFTWARE
 ALGORITHMS
 DIFFICULTIES
 APPLICATIONS
 REFERENCES

2. INTRODUCTION
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.
In recent years (ANPR) have become a reliable and affordable state-
of-the-art technique. They are used by the police for the enforcement
of traffic rules or for crime detection. In London ANPR-systems are
applied to register the vehicles entering the congestion charging zone.
They are used by various police forces and as a method of electronic
toll collection on paper use roads, and monitoring traffic activity such
as red light adherence in an intersection.
ANPR is sometimes known by various other terms:
Automatic licenseplate recognition (ALPR)
Automatic licenseplate reader (ALPR)
Automatic vehicle identification (AVI)
Car plate recognition (CPR)
Licenseplate recognition (LPR)
Lecture automatique de plaques d'immatriculation (LAPI) [Mexico]

3. Mobile licenseplate reader (MLPR)
Vehicle licenseplate recognition (VLPR)
Development History
ANPR was invented in 1976 at the Police Scientific Development
Branch in the UK. Prototype systems were working by 1979, and
contracts were let to produce industrial systems, first at EMI
Electronics, and then at Computer Recognition Systems (CRS) in
Wokingham, UK. Early trial systems were deployed on the A1 road
and at the Dartford Tunnel. However it did not become widely used
until new developments in cheaper and easier to use software was
pioneered during the 1990s. The first arrest through detection of a
stolen car was made in 1981 and the first documented case of ANPR
in helping solve a murder occurred in November 2005 after the
murder of Sharon Beshenivsky, in which City of Bradford based
ANPR played a vital role in locating and subsequently convicting her
killers.
COMPONENTS
The software aspect of the system runs on standard home computer
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 then optical character
recognition (OCR) to extract the alpha numeric.
The font on Dutch plates was changed to improve plate recognition.
The Dubai police use ANPR cameras to monitor vehicles in front and
either side of the patrol car alpha numerics of the license plate. ANPR
systems are generally deployed in one of two basic approaches: one
allows for the entire process to be performed at the lane location in
realtime, and the other transmits all the images from many lanes to a
remote computer location and performs the OCR process there at
some later point in time. When done at the lane site, the information
captured of the plate alphanumeric, date time,lane identification, and

4. any other information required is completed in approximately 250
milliseconds. This information can easily be transmitted to a remote
computer for further processing if necessary, or stored at the lane for
later retrieval. In the other arrangement, there are typically large
numbers of PCs used in a server farm to handle high workloads, such
as those found in the London congestion charge project. Often in such
systems, there is a requirement to forward images to the remote
server, and this can require larger bandwidth transmission media.
TECHNOLOGY
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
license plate arrangements use variations in font sizes & 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 roadrule enforcement or
closedcircuit television cameras, as well as mobile units, which are
usually attached to vehicles Some systems use infrared cameras to
take a clearer image of plates.

5. SYSTEM DESCRIPTION
ANPR-systems for the recording of number plates of vehicles
normally consist of two components. Firstly, a camera that detects
passing vehicles and continuously sends the images to a computer.
Secondly, software that recognises number plates with its characters
and stores them in a database. Some websites of ANPR-System
contractors are listed in the Annexure
CAMERA
The Camera itself consists of an infrared detecting camera, a general
optical colour detecting camera and an infrared light emitting array of
LEDs. The LED array beams infrared light in the direction of the
infrared camera, which then captures the light reflected by the white
background of the number plates of passing by vehicles, which
appears white on the image.
The non-reflecting colour of the characters and the vehicle’s surface
appear black. Direct sunlight enhances the infrared reflection, the
LED array however is bright enough to recognise number plates in
absolute darkness. The focal length of the infrared camera is adjusted
to detect an overall width of one lane. The colour camera with a lesser
focal length generates images for overall view and alignment of the
whole camera body. Both images are sent in intervals of 300ms to a
Computer, where the installed software processes them. ANPR-
systems can be either set up as shown in Figure on a bridge
construction over a carriage way or on the hard shoulder of a
carriageway.
In the latter case it is not possible to detect traffic on two lanes
because the further lane will not be recognizes optimally due to
shadowing effects. As of 2006 systems can scan number plates at
around one per second on cars travelling up to 100 mph (160km/h).

6. NDI-Sidewinder-infrared-camera-night-vision-ANPR camera
SOFTWARE
As soon as the software recognizes an image with a number plate, the
full string is identified by an optical character recognition algorithm
and is checked for international plate syntax to determine the country
of origin. Afterwards the number plate string is saved in conjunction
with a timestamp and the ambiance image of the colour-camera to a
database.

7. ALGORITHMS
1. Plate localisation responsible for finding and isolating the plate on
the picture
2. Plate orientation and sizing compensates for the skew of the plate
and adjusts the dimensions to the required size
3. Normalisation adjusts the brightness and contrast of the image
4. Character segmentation finds the individual characters on the plates
5. Optical character recognition
6. Syntactical/Geometrical analysis check characters and positions
against country specific rules
7. The averaging of the recognised value over multiple fields/images to
produce a more reliable or confident result. Especially since any
single image may contain a reflected light flare, be partially obscured
or other temporary effect.
The complexity of each of these subsections of the program
determines the accuracy of the system. During the third phase
(normalization), 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.
DIFFICULTIES
* Poor file 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.
* Poor image resolution, usually because the plate is too far away but
sometimes resulting from the use of a low quality camera.
* Poor lighting & low contrast due to overexposure, reflection or
shadows
* Object obscuring the plate, quite often a bumper, or dirt on the plate
* A different font, popular for vanity plates
* Circumvention techniques

8. * Lack of coordination between countries or states. Two cars from
different countries or states can have the same number but different
design of the plate.
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.
APPLICATIONS of ANPR
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.
 Parking
One of the main applications of ANPR is parking automation and
parking security: ticketless parking fee management, parking access
automation, vehicle location guidance, car theft prevention, "lost
ticket" fraud, fraud by changing tickets, simplified, partially or fully
automated payment process, among many others.
 Access Control
Access control in general is a mechanisms for limiting access to areas
and resources based on users' identities and their membership in
various predefined groups. Access to limited zones, however, may
also be managed based on the accessing vehicles alone, or together

9. with personal identity. License plate recognition brings automation of
vehicle access control management, providing increased security, car
pool management for logistics, security guide assistance, event
logging, event management, keeping access diary, possibilities for
analysis and data mining.
 Motorway Road Tolling
Road Tolling means, that motorists pay directly for the usage of
particular segment of road infrastructures. Tolls are a common way of
funding the improvements of highways, motorways, roads and
bridges: tolls are fees for services. Efficient road tolling increases the
level of related road services by reducing travel time overhead,
congestion and improve roadways quality. Also, efficient road tolling
reduces fraud related to non payment, makes charging effective,
reduces required manpower to process events of exceptions. License
plate recognition is mostly used as a very efficient enforcement tool,
while there are road tolling systems based solely on license plate
recognition too.
 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 investigatable databases of border crossings,
alarming on suspecious passings, at many more.

10.  Journey Time Measurement
Journey Time Measurement is a very efficient and widely usable
method of understanding traffic, detecting conspicuous situations and
events, etc. A computer vision based system has its well knwon
downfalls in Journey Time Measurement, while Automatic Number
Plate Recognition has provied its viability: vehicle journey times can
be measured reliably by automatic number plate recognitionbased
systems. Data collected by license plate recognition systems can be
used in many ways after processing: feeding back information to
road users to increase traffic security, helping efficient law
enforcement, optimising traffic routes, reducing costs and time, etc.
 Law Enforcement
ANPR is an ideal technology to be used for law enforcement
purposes. It is able to automatically identify stolen cars based on the
upto date blacklist. Other very common law enforcement applications
are red light enforcement and over speed charging and bus lane
control.
 Countries using ANPR Technology in Police Enforcement
* United States [Homeland Security]
* United Kingdom
* Australia
* Belgium
* Denmark
* France
* Germany
* Hungary
* Turky
* Ukraine
* Saudi Arabia
* Sweeden

11. Other Uses
ANPR systems may also be used for/by:
*Section control, to measure average vehicle speed over longer
distances.
*Border crossings.
*Automobile repossessions.
*Petrol stations to log when a motorist drives away without paying for
their fuel.
*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.
*Analyses of travel behaviour (route choice, origin destination etc.)
for transport planning purposes
*Drive Through Customer Recognition, to automatically recognize
customers based on their license plate and offer them the items they
ordered the last time they used the service.
*To assist visitor management systems in recognizing guest vehicles.
*Police and Auxiliary Police
*Car parking companies
*Hotels

12. REFERRENCS
* https://en.wikipedia.org/wiki/Automatic_number_plate_recognition
* https://www.anu.edu.au/Roger.Clarke/DV/ANPR-Surv
* ANPR : Seminar Report and PPT for ECE Students
* Flitsers.net (http://trajectcontroles.net/#)
* ANPR Tutorial (http://www.anprtutorial. com/). ANPR Tutorial.
15 August 2006. Retrieved 24-01-2012
* ANPR FOR THE OBSERVANCE OF TRAVEL BEHAVIOUR
8th International Conference on Survey Methods in Transport,
France, May 25-31,2008 [pdf].
* A Real-Time Malaysian Automatic License Plate
Recognition (M-ALPR) using Hybrid Fuzzy
IJCSNS International Journal of Computer Science and Network
Security, VOL.9 No.2, February 2009
* A Realtime vehicle License Plate Recognition (LPR)"
(http://visl.technion.ac.il/projects/2003w24/). VISL, Technion, 2003
* An Approach To License Plate Recognition"
(http://pages.cpsc.ucalgary.ca/~federl/Publications/licensePlate1996/li
censeplate1996 ) (PDF). University of Calgary. 1996
* Vehicle registration plates of Saudi Arabia