On Saturday January 22, 2011, at about 10:00 PM, an officer from the Coachella Police Department was driving in a marked unit equipped with an Automated License Plate Reader (ALPR) near Grapefruit Blvd. and Avenue 52. This device can scan the license plates of vehicles and compare them automatically to wanted vehicle databases. The ALPR system picked up a stolen white van occupied by a male adult driver. After confirming the vehicle had been stolen out of Rancho Mirage, the officer attempted to stop the driver, who immediately fled at a high rate of speed. A pursuit was initiated and the suspect finally crashed into a fence near Desert Cactus and Airport Blvd., in Thermal. The suspect, Martin Chapa, 31 years out of Coachella, was on active state parole with multiple past felony contacts and he was taken into custody without incident.
The Coachella Police Department uses a variety of Community Policing strategies to reduce the fear of crime in the city. The use of the Automated License Plate Reader system is just one example how we use technology to increase efficiency. We would like to remind everyone to report any suspicious activity by calling 911, or by contacting our dispatch at (760) 836-3215. Anonymous information can be provided through Crime Stoppers at (760) 341-STOP, or by sending us email at IndioStation@riversidesheriff.org and refer to case Y110220053.
Automatic number plate recognition (ANPR; see also other names below) 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 cataloging the movements of traffic or individuals.
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. ANPR technology tends to be region-specific, owing to plate variation from place to place.
Concerns about these systems have centered on privacy fears of government tracking citizens’ movements, misidentification and high error rates.
In the United States, ANPR systems are more commonly referred to as ALPR (Automatic License Plate Reader/Recognition) technology, due to differences in language (i.e. “number plates” are referred to as “license plates” in American English)
Jurisdictions in the U.S. have stated a number of reasons for ALPR surveillance cameras, ranging from locating drivers with suspended licenses or no insurance, to finding stolen vehicles and “Amber Alerts”. With funding from the insurance lobby, Oklahoma introduced ALPR with the promise of eliminating uninsured motorists, by integrating it with its existing PikePass hybrid RFID/OCR toll collection system, and unmarked police vehicles used for intelligence gathering.   Oklahoma replaced all license tags with ALPR-compatible plates in 2009. In Arizona, insurance companies are helping to fund the purchase of ALPR systems for their local law enforcement agencies to aid in the recovery of stolen vehicles.
Other ALPR uses include parking enforcement, and revenue collection from individuals who are delinquent on city or state taxes or fines.
A recent initiative by New York State deployed ALPR systems to catch car thieves by tracing suspect plates back to forged documents. Albany, NY police also scan vehicles in their parking lot to check visitors for warrants.
In addition to the real-time processing of license plate numbers, ALPR systems in the US collect (and indefinitely store) data from each license plate capture. Images, dates, times and GPS coordinates can be stockpiled and can help place a suspect at a scene, aid in witness identification, pattern recognition or the tracking of individuals. Such data can be used to create specialized databases that can be shared among departments or individuals (such as insurers, banks or auto recovery “repo-men”. Specialized databases can also be used to compile personal information on individuals such as journalists  suspected gang members, employees of a business, patrons of a bar, etc., and be shared by E-mail or portable flash media.
One of the biggest challenges with ALPR technology in the US is the accuracy of the Optical Character Recognition (OCR)—the actual identification of the characters on the license plate. Many variables affect OCR accuracy, starting with the fact that each state has multiple license plate designs that must be recognized by the ALPR system. Also, the shape of the characters, color of the plates and whether the characters are raised or flat can affect accuracy. Many times the letter D is mistaken for a Q or an O and some colors, especially reddish tones, are hard to read and as a result many system vendors will quote accuracy rates that are misleading. So potential buyers must be wary of any quoted % rates and ask what they mean as you will find that 90% really means 90% (N-1 or N-2). This little detail in the brackets (which will not be either obvious or explained up front) allows the vendor to get all characters in a plate correct except one (N-1) or two (N-2).
From time to time, states will make significant changes in their license plate protocol that will affect OCR accuracy. They may add a character or add a new license plate design. ALPR systems must adapt to these changes quickly in order to be effective. For the most part, however, the North American design will be based on a variation of the “Zurich Extra Condensed” font.
Another challenge with ALPR systems is that some states have the same license plate protocol. For example more than one state may use three letters followed by four numbers. So each time the ALPR systems alarms, it is the user’s responsibility to make sure that the plate which caused the alarm matches the state associated with the license plate listed on the in-car computer.
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?”
Systems with a simple review step are thought by some[who?] to eliminate this argument. Then the machine reports data – date, time, speed measurement and license plate – a good system records a photo of the event – so a person presented with the data is making an accusation. You will get a copy of the data when you go to court.
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. The electronic surveillance system produces tickets which in the US are often in excess of $100, and are virtually impossible for a citizen to contest in court without the help of an attorney. The revenues generated by these machines are shared generously with the private corporation that builds and operates them, creating a strong incentive to tweak the system to generate as many tickets as possible.
Older systems had been notably unreliable; in the UK this has been known to 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 offense. Improvements in technology have drastically decreased error rates, but false accusations are still frequent enough to be a problem.
Perhaps the best known incident involving the abuse of an ANPR database in North America is the case of Edmonton Sun reporter Kerry Diotte in 2004. Diotte wrote an article critical of Edmonton police use of traffic cameras for revenue enhancement, and in retaliation was added to an ANPR database of “high-risk drivers” in an attempt to monitor his habits and create an opportunity to arrest him. The police chief and several officers were fired as a result, and The Office of the Privacy Commissioner of Canada expressed public concern over the “growing police use of technology to spy on motorists.” 
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 along with similar legislation (see personally identifiable information). The laws in the UK are strict for any system that uses CCTV footage and can identify individuals.
There is also a case in the UK for saying that use of ANPR cameras is against the law under the Regulation of Investigatory Powers Act 2000. The breach exists, some say, in the fact that ANPR is used to monitor the activities of law-abiding citizens and treats everyone like the suspected criminals intended to be surveyed under the act. The police themselves have been known to refer to the system of ANPR as a “24/7 traffic movement database” which is a diversion from its intended purpose of identifying vehicles involved in criminal activities.