automatic license plate identifier ANPR ; see also other names below) is a technology that uses optical character recognition in images to read vehicle registration plates to create vehicle location data. It can use existing closed-circuit television, road rule enforcement cameras, or cameras specifically designed for the task. ANPR is used by police forces around the world for law enforcement purposes, including to check whether the vehicle is registered or licensed. It is also used for the collection of electronic tolls on the road pay-per-use and as a method of cataloging traffic movements, for example by highway agencies.
Automatic number plate recognition can be used to store images captured by the camera as well as text from the plate, with some configured to store driver's photos. Systems generally use infrared illumination to allow the camera to take pictures at any time of the day or night. ANPR technology should consider plate variations from one place to another.
Concerns about the system center on government privacy concerns that track citizen movements, misidentification, high error rates, and increased government spending. Critics describe it as a form of mass oversight.
Video Automatic number-plate recognition
Nama lain
ANPR is sometimes known by a variety of other terms:
- Recognition of automatic (or automatic) plates (ALPR)
- Automatic (or automatic) license plate reader (ALPR)
- Automatic vehicle identification (AVI)
- Car license recognition (CPR)
- Platform introduction (LPR)
- Course on automatique de plaques d'immatriculation (LAPI)
- Mobile number reader (MLPR)
- Vehicle license plate identifier (VLPR)
- Identify vehicle recognition (VRI)
Maps Automatic number-plate recognition
Development
ANPR was discovered in 1976 at the Police Scientific Development Branch in England. The prototype system worked in 1979, and contracts were awarded to produce industrial systems, first at EMI Electronics, and then at Computer Recognition Systems (CRS) in Wokingham, England. An early pilot system was deployed on A1 and in the Dartford Tunnel. The first arrests through the detection of stolen cars were made in 1981. However, ANPR was not widely used until new developments in cheaper and easy-to-use software were pioneered during the 1990s. ANPR data collection for future use ( i
Components
Aspects of system software run on standard home computer hardware and can be connected to other applications or databases. It first uses a series of image manipulation techniques to detect, normalize and enhance the number plate image, and then optical character recognition (OCR) to extract alphanumeric number plates. The ANPR system is generally used in one of two basic approaches: one allows for the entire process to be performed in a real-time path location, and the other transmits all images from multiple paths to a remote computer location and performs the OCR process at some point time later. When done on the path site, information retrieved from the alphanumeric plate, date, path identification, and other necessary information is completed in about 250 milliseconds [need citation] . This information can be easily transmitted to a remote computer for further processing if necessary, or stored in the lane for later retrieval. In other settings, there is usually a large number of PCs used on a server farm to handle high workloads, such as those found in London's congestion cost project. Often in such systems, there is a requirement to forward images to a remote server, and this can require a larger bandwidth transmission medium.
Technology
ANPR uses optical character recognition (OCR) on images taken by the camera. When the Dutch vehicle registration plates switched to different styles in 2002, one of the changes made was on the font, introducing small gaps in some letters (such as P and R ) to make it more different and therefore more readable to such a system. Some plate settings use font size variation and position - the ANPR system must be able to resolve the differences in order to be truly effective. More complicated systems can address international variants, although many programs are individually designed for each country.
The cameras used can be either rule-guarded road rules or closed-circuit television cameras, as well as mobile units, which are usually attached to vehicles. Some systems use infrared cameras to take clearer plate pictures.
On mobile system
During the 1990s, significant advances in technology took automatic plate number recognition (ANPR) systems from expensive, unruly, and fixed applications for simple mobile "point and firing". This is made possible by the manufacture of software running on a cheaper, non-specialized hardware-based PC that is no longer required to be given a predetermined angle, direction, size and speed at which the plate will pass through the viewing camera field. The further components that are scaled down at more cost-effective pricing points cause the number of records distributed by law enforcement agencies around the world. Smaller cameras with the ability to read number plates at higher speeds, along with smaller, more durable processors that fit the police vehicle rod, allow law enforcement officers to patrol each day with the benefit of plate readings in real time, when they can ban immediately.
Despite its effectiveness, there are important challenges associated with mobile ANPR. One of the biggest is that the processor and camera should work fast enough to accommodate a relative speed of over 100 mph (160 km/h), a possible scenario in case of oncoming traffic. This equipment should also be very efficient because the power source is a vehicle battery, and the equipment must be small to minimize the space it needs.
Relative speed is just one of the problems that affect the camera's ability to actually read the license plate. The algorithm should be able to compensate for all variables that may affect ANPR's ability to produce accurate readings, such as time, weather and angle between the camera and the license plate. The system's wavelength light can also have a direct impact on the resolution and readability accuracy under these conditions.
Installing ANPR cameras in law enforcement vehicles requires careful consideration of the camera alignment to the number plate they should read. Using the right number of cameras and positioning them accurately for optimal results can be a challenge, given the various missions and environments at hand. A highway patrol requires a front-facing camera that reaches multiple paths and can read license plates at very high speeds. City patrols require shorter distances, lower-focus cameras to catch plates on parked cars. Parking spaces with parked cars perpendicular often require special cameras with very short focal lengths. Most advanced systems are technically flexible and can be configured with a number of cameras ranging from one to four that can be easily repositioned as needed. The country with the back number plate alone has additional challenges because the front-facing camera is ineffective with incoming traffic. In this case one camera can be rotated backwards.
Algorithm
There are seven major algorithms that software needs to identify the license plate:
- Localize the plates - responsible for locating and isolating plates in the drawing.
- Orientation and size of plates - compensates for plate slope and adjusts dimensions to required size.
- Normalization - adjust the brightness and contrast of the image.
- Character segmentation - find individual characters in the lemping.
- Optical character recognition.
- Syntactic/Geometric Analysis - check character and position against country-specific rules.
- Average of recognized values ​​in different fields/images to produce more reliable or confident results. Especially since a single image can contain reflected light beacons, some obscured or other temporary effects.
The complexity of each of these program subsections determines the accuracy of the system. During the third phase (normalization), some systems use edge detection techniques to increase the image difference between letters and plates. The median filter can also be used to reduce visual disturbances in images.
Difficulty
There are a number of possible difficulties that the software must overcome. These include:
- Bad file resolution, usually because the disk is too remote but sometimes resulting from the use of low quality cameras.
- The image is blurry, especially motion blur.
- Bad lighting and low contrast due to over-illumination, reflection, or shadow.
- An object that obscures (part of) the plate, quite often in the form of a crane rod, or dirt on a plate.
- Read different license plates in front and back as trailers are towed, camped, etc.
- Change of vehicle path in camera viewpoint during plate readings.
- Different fonts, popular for vanity plates (some countries do not allow such plates, eliminating problems).
- Counting technique.
- Lack of coordination between countries or countries. Two cars from different countries or states can have the same number but different plate designs.
While some of these problems can be fixed in the software, it is mainly left to the hardware side of the system to find solutions to these difficulties. Increasing the height of the camera can avoid problems with objects (like other vehicles) obscuring plates but introducing and increasing other problems, such as adjusting to increase the slope of the plate.
In some cars, the tow bar can obscure one or two characters from the number plate. Bicycles on bicycle racks can also obscure license plates, although in some countries and jurisdictions, such as Victoria, Australia, "bike plates" should be installed. Some small-scale systems allow some errors on the license plate. When used to provide special vehicle access to the barricade area, a decision can be made to have an error rate of one of the acceptable characters. This is because the possibility of an unauthorized car having a similar number plate looks quite small. However, this level of inaccuracy will not be accepted in most ANPR system applications.
Imaging hardware
At the front end of any ANPR system is imaging hardware that captures the image of the license plate. Initial shooting forms a very important part of the ANPR system which, according to the waste in it, removes the computational principle, will often determine the overall performance.
Capture of the plate is usually done by a special camera designed specifically for the task, although new software techniques are being implemented that support I.P. based surveillance cameras. and improve the ANPR utility for perimeter security applications. The factors that cause difficulties for the camera's imaging plate include the speed of the vehicle being recorded, the various levels of ambient light, the lights of the lamp and the harsh environmental conditions. Special number plate capture cameras will incorporate infrared illumination to solve lighting problems and plate reflectivity.
Many countries now use reverseflective number plates. It returns the light back to the source and thus increases the image contrast. In some countries, the characters on the plate do not reflect, providing a high contrast level with the reflective background in any lighting conditions. Cameras that use active infrared imaging (with normal color filters above the lens and the infrared illuminator next to it) are very useful because infrared waves are reflected back from the plates. This is possible only on special ANPR cameras, and hence cameras used for other purposes should rely more on software capabilities. Furthermore, when a colorful image is required as well as the use of ANPR-retrieved details, it is necessary to have one infrared-capable camera and one normal camera (color) work together.
To avoid blurring, it is ideal to have a dedicated camera shutter speed that is set to 1/1000 sec. It is also important that the camera uses a global shutter, compared with a rolling shutter, to ensure that the images taken are distortion free. As the car moves, a slower shutter speed can produce images that are too blurry to read using OCR software, especially if the camera is much higher than the vehicle. In slow moving traffic, or when the camera is at a lower level and the vehicle is at an angle close to the camera, the shutter speed does not need to be too fast. Shutter speed 1/500 second can overcome traffic moving up to 40 mph (64 km/h) and 1/250 seconds to 5 mph (8 km/h). The camera capture plate can produce usable images from vehicles traveling at speeds of 120 mph (190 km/h).
To maximize the chance of effective number plate retrieval, the installer should carefully consider the camera position relative to the target catchment area. Exceeding the incident threshold between the camera lens and the plate will greatly reduce the chances of obtaining a usable image due to distortion. Manufacturers have developed tools to help eliminate errors from the physical installation of plate catch cameras.
Usage
Law enforcement
Australia
Some State Police Forces, and Department of Justice (Victoria) use fixed and moving ANPR system. The New South Wales Police Highway Patrol was the first to be tried and used a fixed ANPR camera system in Australia in 2005. In 2009 they began the launch of the ANPR mobile system (officially known as MANPR) with three infrared cameras mounted to the Highway Patrol fleet. This system identifies unlisted and stolen vehicles as well as disqualified or suspended drivers and other 'interested persons' such as those with tremendous warrants.
Belgium
Mechelen City uses ANPR system since September 2011 to scan all cars crossing city limits (in and out). Cars listed on the 'black list' (no insurance, stolen, etc.) Generate alarms in the shipping space, so they can be intercepted by patrols. As of early 2012, 1 million cars per week are automatically checked in this way.
Canada
The police service in Ontario uses automatic plate recognition software to catch the driver behind the wheel of a vehicle with Ontario plates.
Denmark
This technique was tested by Danish police. It will be used permanently from the end of 2015.
French
180 handsome on the main roads have been built all over the country. This along with 250 other fixed cameras is to allow environmental taxes on trucks over 3.5 tonnes. The system is currently being challenged and while they may collect data about vehicles passing through cameras, no environmental taxes are charged.
German
On March 11, 2008, the Federal Constitutional Court of Germany ruled that some areas of the law that permit the use of automatic license plate recognition systems in Germany violate the right to privacy. More specifically, the court found that storing any information (that is, the number plate data) that is not for pre-destined use (for example, to track the tracking of terrorist suspects or for speeding law enforcement) is a violation of Germany. law. This system is provided by Jenoptik Robot GmbH, and is called TraffiCapture.
Hungarian
In 2012 a state consortium was established between the Hungarian Ministry of Home Affairs, National Police Headquarters and the Central Commission for Public Administration and Electronic Services with the aim of installing and operating an integrated intelligent transportation system (ITS ) with national coverage on end of 2015. Inside the system, 160 portable traffic enforcement and data collection units and 365 permanent gantry installations are brought online with ANPR, speed detection, imaging and statistical capabilities. As all data points are connected to centralized ITS, each consortium member can separately use various administrative and enforcement activities, such as remote vehicle registration and insurance verification, speed enforcement, traffic lanes and lights, and desired or vehicle interruptions stolen between other.
Some Hungarian auxiliary police units also use a system called Matrix Police in cooperation with the police. It consists of a portable computer equipped with a web camera that scans the stolen car database using automatic license plate recognition. The system is installed in the dashboard of the selected patrol vehicle (a handheld based PDA version also exists) and is mainly used for controlling car parking plates. Because the Maid Pole does not have the authority to order a moving vehicle to stop, if a stolen car is discovered, the police officially notified.
Pakistan
This technique was proposed by the Lahore Police; if approved will work in 2018.
Saudi Arabia
The vehicle registration plates in Saudi Arabia use a white background, but some vehicle types may have different backgrounds. US diplomatic plates have the letter 'USD', which in Arabic reads 'DSU' when read from right to left in the direction of Arabic writing. There are only 17 Arabic letters used on the registration plate. The challenge for plate recognition in Saudi Arabia is the size of its digits. Some plates use East Arabic numerals and are equivalent to 'Western Arab'. Research with source code is available for Arab Arabic APNR.
Swedish
This technique was tested by the Swedish Police Authority in nine different locations in Sweden.
Turkish
Several cities have been tested - and some have been used - KGYS (Kent Guvenlik Yonetim Sistemi, City Security Administration System), [3], the capital of Ankara, has debuted KGYS - which consists of a registration plate registration number system on the main arteries and exits city. This system has been used with two cameras per lane, one for plate recognition, one for speed detection. Now the system has been widened to connect all camera registration numbers, and enforce the average speed from a predetermined distance. Some arteries have a limit of 70 km/h (43 mph), and about 50 km/h (31 mph), and photo proof with date-time details posted to the registration address if a speed violation is detected. In 2012, a fine to exceed the speed limit for more than 30% is approximately US $ 175.
Ukraine
System integration project Ã,  «OLLI Technology» and the Ministry of Internal Affairs of the Ukrainian Ministry of State Traffic Inspection (STI) experiment on the introduction of modern technical complex capable of finding stolen cars, unplugged drivers driving license and other troubled cars in real time. "Video Control" Ukrainian complex that works with the principle of video mounting the car with the recognition of the license plate with a check under the database.
United Kingdom
The Home Office states the purpose of automatic license plate recognition in the UK is to help detect, deter and interfere with criminality including dealing with organized crime and terrorist groups. The movement of vehicles is recorded by a network of nearly 8000 cameras that record between 25 and 30 million ANPR 'reads' of notes each day. These records are kept for up to two years at the National ANPR Data Center, which can be accessed, analyzed and used as evidence as part of an investigation by a UK law enforcement agency.
In 2012, the British Parliament passed the Freedom of Protection Act which includes several provisions relating to the control and limitation of the collection, storage, retention and use of information about individuals. Under this Act, the Central Office issues its code of practice in 2013 for the use of surveillance cameras, including ANPR, by governments and law enforcement agencies. The purpose of this code is to help ensure its use "is marked as oversight by consent, and such approval on the part of the public shall be approved and not assumed by the operator of the system." Supervision oversight shall be regarded as analogous to the police with consent. "In addition, a set of standards introduced in 2014 for data, infrastructure, and data access and management.
United States
In the United States, the ANPR system is more commonly referred to as the ALPR (Automatic License Plate Reader/Recognition) technology, because language differences (ie, "license plates" are referred to as "license plates" in American English)
The use of cellular ANPR is widespread among US law enforcement agencies at city, district, state and federal levels. According to a 2012 report by the Police Executive Research Forum, about 71% of all US police departments use some form of ANPR. Mobile ANPR becomes a significant component of urban predictive policing strategy and intelligence gathering, as well as for restoration of stolen vehicles, identification of wanted criminals, and income collection from tax or city or state delinquent, or monitoring for "Yellow Signs". With the widespread application of this technology, many US states are now issuing mild infringement quotes of up to $ 500 when license plates are identified as out of date or in the wrong vehicle. Identifiable plates can be matched to the database including "wanted people", "protection orders", missing persons, gang members, known and suspected terrorists, supervised release, immigration offenders, and National Gender Offenders list. In addition to real-time number plate number processing, ANPR systems in the US collect (and can store indefinitely) data from each number plate catch. GPS pictures, dates, times and coordinates can be stockpiled and can help locate suspects at the scene, assist in witness identification, pattern recognition or individual tracking.
The Department of Homeland Security has proposed a federal database to incorporate all monitoring systems, which are canceled after a privacy complaint. In 1998, a Washington police lieutenant D.C. pleaded guilty to extortion after extorting owners of vehicles parked near a gay bar. By 2015, the Los Angeles Police Department proposes sending letters to the home address of all vehicles entering high prostitution areas.
Early ANPR private sector applications have been used for vehicle repossession and recovery), although the application of ANPR by private companies to collect information from private-owned vehicles or collected from private properties (eg, driveways) has become a matter of public sensitivity and debate.. Other uses of ANPR include parking enforcement, and revenue collection from individuals in arrears with city or state taxes or penalties. This technology is often featured in the reality show TV Wars Parking displayed on A & amp; E Network. In the event, tow truck drivers and boot teams use ANPR to find winding vehicles with large unpaid parking fines.
Legal
Laws vary between states regarding the collection and storage of plate information. By 2018, 14 countries have limits on how long data can be maintained, with the lowest being New Hampshire (3 minutes) and Colorado (3 years). The Virginia Supreme Court ruled in 2018 that data collected from the ALPR could be private information.
Camera with average speed
ANPR is used for speed limit enforcement in Australia, Austria, Belgium, Dubai (UAE), France, Italy, Netherlands, Spain, South Africa, England, and Kuwait.
This works by tracking the travel time of the vehicle between two fixed points, and calculating the average velocity. These cameras are claimed to have an advantage over traditional speed cameras in maintaining a steady legal speed over long distances, rather than pushing heavy braking on approaches to specific camera locations and subsequent acceleration back to illegal speeds.
Italy
On Highway Italy has developed a monitoring system called Tutor that covers more than 2500 km (2012). Tutor system is also able to intercept the car while changing lanes.
Dutch
The average speed camera ( trajectcontrole ) is in the Netherlands since 2002. In July 2009, 12 cameras operate, mostly in the west of the country and along the A12. Some of them are divided into several "sections" to allow cars to leave and enter the highway.
A first experimental system was tested on a short stretch of A2 in 1997 and was considered a great success by police, reducing excess speed to 0.66%, compared to 5 to 6% when regular speed cameras were used in the same location. The first permanent average speed camera was installed on the A13 in 2002, shortly after the speed limit was reduced to 80 km/h to limit noise and air pollution in the area. In 2007, the average speed of the camera produced 1.7 million penalties for overspeed out of a total of 9.7 million. According to the Dutch Attorney General, the average number of speed limit violations on toll road portions equipped with average speed cameras is between 1 and 2%, compared with 10 to 15% elsewhere.
United Kingdom
One of the most prominent of the average speed cameras in the UK was found on the A77 road in Scotland, with 32 miles (51 km) being monitored between Kilmarnock and Girvan. In 2006 it was confirmed that fast-paced tickets could be avoided from 'SPECS' cameras by changing lanes and the RAC Foundation feared that people might play a "Russian Roulette" that went from one path to another to reduce their chances of being caught. However, in 2007 the system was upgraded for multi-lane use and in 2008 the manufacturer described the "myth" as "completely incorrect". There is evidence that the application of systems such as SPECS has a profound effect on the volume of drivers driving at excessive speeds; on the stretch of road mentioned above (A77 Between Glasgow and Ayr) there has been a record of "big declines" in ongoing violations since the introduction of the SPECS system.
Criminals
Recent innovations have contributed to the adoption of ANPR for perimeter security and access control applications at government facilities. In the US, "domestic security" efforts to protect against alleged "acts of terrorism" have resulted in the adoption of ANPR for sensitive facilities such as embassies, schools, airports, maritime ports, military and federal buildings, law enforcement and government facilities, and transportation hubs. ANPR is marketed as applicable through an IP-based surveillance camera network that performs a "dual task" with face recognition, object tracking, and recording systems for the purpose of monitoring suspicious behavior or anomalies, improving access control, and matching to monitoring lists. ANPR systems are most often installed at significant points of sensitivity, entry or exit. Major US agencies such as the Department of Homeland Security, the Department of Justice, the Department of Transportation and the Department of Defense have purchased ANPR for perimeter security applications. A large network of ANPR systems is being installed by cities like Boston, London and New York City to provide citywide protection against acts of terrorism, and to provide support for public meetings and public spaces.
The Center for Evidence-Based Crime Policy at George Mason University identifies randomized controlled trials with automatic plate recognition recognition technology as very strict.
Enterprise security and services
In addition to government facilities, many private sector industries with facility security issues began implementing ANPR solutions. Examples include casinos, hospitals, museums, parking facilities, and resorts. In the US, private facilities typically can not access government or police surveillance lists, but can develop and match with their own databases for customers, VIPs, critical personnel or "prohibited persons" lists. In addition to providing perimeter security, the private ANPR has service applications for valet/customer recognized and VIP recognition, logistics and tracking of key personnel, sales and advertising, parking management, and logistics (vendor and vehicle tracking support).
Traffic control
Many cities and districts have developed traffic control systems to help monitor the movement and flow of vehicles around the road network. This usually involves looking at historical data, estimates, observations and statistics, such as:
- Car park use
- Use of pedestrian crossings
- Number of vehicles along the road
- Areas with low and high congestion
- The frequency, location, and cause of the road work
CCTV cameras can be used to help traffic control centers by providing them with live data, enabling traffic management decisions to be made in real-time. By using ANPR on these recordings it is possible to monitor individual vehicle trips, automatically providing information on the speed and flow of various routes. These details can highlight problem areas when and occur and help the center to make informed incident management decisions.
Several countries in the UK have been working with Siemens Traffic to develop a traffic monitoring system for their own control center and for the public. Projects such as ROMANSE The Hampshire City Council provides an interactive and real-time website that shows details about the city's traffic. This site displays information about car parks, ongoing road works, special events, and recordings taken from CCTV cameras. An ANPR system can be used to provide the average point-to-point travel time along a particular route, which can be displayed on a variable message flag (VMS) that gives the driver the ability to plan their route. ROMANSE also allows travelers to view the current situation using a mobile device with an Internet connection (such as WAP, GPRS or 3G), enabling them to view images of CCTV mobile devices in the Hampshire road network.
British company Trafficmaster has been using ANPR since 1998 to estimate average traffic speeds on non-highway roads with no results affected by local fluctuations caused by traffic lights and similar. The company now operates a network of over 4000 ANPR cameras, but claims that only the four most central digits are identified, and no parent data numbers are retained.
The IEEE Intelligent Transportation Systems Society publishes several papers on the technology and application of plate number recognition.
Collection of electronic pulses
Highway
Tolway Ontario 407 ETR uses a combination of ANPR and radio transponders to incoming and out-of-way toll vehicles. The radio antenna is located at each intersection and detects the transponder, noting the unique identity of each vehicle in the same way as the ANPR system. Without ANPR as a second system, it is impossible to monitor all traffic. Drivers who choose to rent transponders with C $ 2.55 per month are not charged a "Video Toll Charge" fee of C $ 3.60 for road use, with heavy vehicles (those with gross weighs over 5,000 kg) are required to use them. Using a good system, highway users are notified of postage usage charges.
There are many other electronic toll collection networks that use this combination of radio frequency identification and ANPR. These include:
- The Golden Gate Bridge in San Francisco, California, began using an electronic toll system incorporating Fastrak and ANPR on 27 March 2013.
- NC Quick Pass for Interstate 540 (North Carolina) Triangle Expressway in Wake County, North Carolina
- Bridge Pass for Saint John Harbor Bridge in Saint John, New Brunswick
- A brisk walk on the Golden Ears Bridge, across the Fraser River between Langley and Maple Ridge
- e-TAG, Australia
- FasTrak in California, United States
- Highway 6 in Israel
- The tunnel in Hong Kong
- Autopista Central in Santiago, Chile (site in Spanish)
- E-ZPass in New York, New Jersey, Pennsylvania, Massachusetts (as Fast Track to 2012), Virginia (formerly Smart Tags), and other states. Maryland Route 200 uses a combination of E-ZPass and ANPR.
- TollTag in North Texas and EZ-Tag in Houston, Texas.
- I-Pass in Illinois
- Pike Pass in Oklahoma
- Peach Pass I-85 Atlanta, GA Gwinnett County
- OGS (Automatic GeÃÆ'§i? Sistemi) is used on Bosphorus Bridge, Fatih Sultan Mehmet Bridge, and Trans European entrance in Istanbul, Turkey
- M50 Westlink Toll in Dublin, Ireland
- Hi-pass in South Korea
- Northern Gateway, SH 1, Auckland, New Zealand
- Evergreen Point Floating Bridge, Seattle, and Washington State Route 167 HOT-lanes in western Washington
- ETC in Taiwan
- SunPass In Florida
Portugal
The Portuguese Road has an old highway with a toll station where drivers can pay by card and also a pathway where there is an electronic collection system. But most new highways only have the option of an electronic toll collection system. The electronic toll collection system consists of three different structures:
- ANPR that works with the infrared camera and reads the license plate of each vehicle
- Lasers for volumetric measurements of vehicles to confirm whether it's an ordinary car or an SUV or truck, since the payload differs according to the vehicle type
- RFID-likes to read smart on-board tags.
When the smart tag is installed in the vehicle, the car is quickly identified and the owner's bank account is automatically deducted. This process is realized at speeds of over 250 km per hour. If the car does not have a smart tag, the driver must go to the payment station to pay the toll between day 3 and 5 after the surplus fee. If he fails to do so, the owner sends a letter home with heavy fines. If this is not paid, it increases fivefold and after that, the car is put into the police database to confiscate the vehicle. The system is also used in some restricted access areas in major cities to allow only entry from previously registered residents. It is planned to be implemented both on more roads and at the entrance of city tolls/access restrictions. The efficacy of the system is considered so high that it is almost impossible for the driver to complain.
London London congestion charges
The cost of congestion in London is an example of a system that requires motorists to enter the payment area. Transportation for London (TfL) uses ANPR system and daily cost driver fee of Ã, Â £ 11.50 if they enter, go or move around the congestion charge zone between 7 am and 6:00 am, Monday through Friday. Reduced fees of Ã, Â £ 10.50 are paid by vehicle owners who sign up for automatic deduction schemes. Fines for traveling within the zone without paying a fee are Ã, £ 65 per violation if paid before the deadline, doubling to Ã, Â £ 130 per violation thereafter.
Currently there are 1,500 cameras that use automatic number plate recognition (ANPR) technology. There are also a number of camera phone units that can be used anywhere in the zone.
It is estimated that about 98% of vehicles moving inside the zone are caught on camera. The video stream is transmitted to data centers located in central London where ANPR software reduces vehicle registration plates. The second data center provides a backup location for image data.
Both front and rear license plates are being captured, on incoming and outgoing vehicles - this gives up to four opportunities to catch license plates of vehicles entering and leaving the zone. The list is then compared to the list of cars that the owner/operator has paid to enter the zone - those who have not paid fined. Registered owners of such vehicles are searched in the database provided by DVLA.
Swedish
In Stockholm, Sweden, ANPR is used for Stockholm congestion taxes, car owners driving in or out of the city center must pay a fee, depending on the time of day. From 2013, also to tax congestion Gothenburg, which also includes vehicles passing through the city on the main highway.
Personal use
Some British companies and agents use the ANPR system. These include Vehicle Service Bodies and Operators (VOSA), Driver and Vehicle License Agency (DVLA) and Transport for London.
Other uses
ANPR system can also be used for/by:
- Control section, to measure the average vehicle speed at greater distances.
- Border crossing
- Motor vehicle takeovers
- The gas station to get in when the driver is driving without paying for fuel.
- Marketing tools to record usage patterns
- Targeted ad, a-la "Minority Report" -style billboard.
- The traffic management system, which determines the flow of traffic using the time it takes the vehicle to pass through two ANPR sites
- Travel behavior analysis (route selection, destination origin etc.) for transportation planning purposes
- Driving Through Customer Recognition, to automatically recognize customers based on their license plate and offer them the items they ordered last time they used the service.
- To assist the visitor management system in recognizing the guest vehicle.
- Police and Police
- Car parking company
- Hotels
- Upholding the Displacement Act for emergency vehicles
- Automatic emissions test
Challenges
Evasion
Vehicle owners have used a variety of techniques in an effort to avoid ANPR systems and road enforcement cameras in general. One method improves the reflective nature of the letters and makes it more likely that the system will not be able to find plates or produce a high enough level of contrast to be able to read them. This is usually done by using a plate cover or spray, although claims about its last effectiveness are debatable. In most areas, the cover is illegal and protected by existing laws, while in most countries there is no law prohibiting the use of sprays. Other users have tried to rub their plates with the ground or use cover to cover the plate.
The new frame around the Texas license plate was made illegal in Texas on September 1, 2003 by the Texas Senate Bill 439 because they caused problems with the ANPR device. The law makes it a Class C crime (punishable with a fine of up to US $ 200), or Class B (punishable with a fine of up to US $ 2,000 and 180 days in jail) if it can be proved that the owner did so intentionally obscures their plate. The law was later clarified in 2007 to allow for new frames.
If the ANPR system can not read plates, it can mark images for attention, with human operators looking to see if they are able to identify the alphanumeric.
To avoid supervision or fines, there has been an increase in car cloning. This is usually achieved by copying the registration plate from another car with the same model and age. This can be difficult to detect, especially since clones can alter registration plates and travel behavior to inhibit investigations.
In 2013 researchers at Sunflex Zone Ltd created a privacy number plate frame that uses near infrared light to make the license plate unreadable to plate recognition systems.
Controversy
The introduction of the ANPR system has caused concerns of misidentification and continuation of the 1984 -style supervision. In the United States, some people like Gregg Easterbrook are opposed to what they call "the engine that issued the speeding ticket and red light ticket" for the start of a slippery slope to the automatic judicial system:
- "A machine classifies a person as a perpetrator, and you can not face your accuser because there are no accusers... can it be wise to establish the principle that when the machine says you are doing something illegal you are considered guilty?"
Similar criticisms have been raised in other countries. Easterbrook also argues that this technology is used to maximize revenue for the country, rather than to promote safety. The electronic surveillance system generates tickets that are in the US often over $ 100, and it is almost impossible for a citizen to take part in a court without the help of a lawyer. The revenues generated by these machines are generously shared with private companies that build and operate them, creating powerful incentives to change the system to generate as many tickets as possible.
The older system is unreliable; in the UK, it is known to cause false accusations with the owner of the vehicle having to pay Ã, Â £ 10 to be issued with evidence (or no) of the offense. Technological improvements have drastically lowered the error rate, but false accusations are still quite often a problem.
Perhaps the most notable incident involving misuse of ANPR database in North America was the case of Kerry Diotte's Edmonton Sunrise reporter in 2004. Diotte wrote a critical article about the use of police traffic cameras in Edmonton for income increase, and in retaliation added to the ANPR database of "high-risk drivers" in an effort to monitor their habits and create opportunities to capture them. The police chief and several officers were dismissed as a result, and the Office of the Canadian Privacy Commissioner expressed public concern over "the increasing use of technology by the police to spy on motorists."
Other concerns include storing information that can be used to identify people and store details about their driving habits and daily life, violating the Data Protection Act in conjunction with similar laws (see identifiable personal information). Laws in the UK are very strict for any system that uses CCTV recordings and can identify individuals.
Also of concern is data security after being mined, following the discovery of missing police surveillance records in the gutter.
There are also cases in the UK that say the use of ANPR cameras is unlawful under the Powers Act 2000 Investigation Act. Such violations exist, some say, in the fact that ANPR is used to monitor the activities of law-abiding citizens and treat everyone like suspected criminals who are intended to be surveyed under the Act. The police themselves have been known to refer to the ANPR system as a "24/7 traffic movement database" which is a diversion from the intended purpose of identifying vehicles involved in criminal activity. The opposite view is that where the plate has been cloned, a 'reading' of an innocent rider vehicle will allow the removal of the vehicle from investigation by visual inspection of the stored image. Likewise, stolen vehicles are read by the ANPR system between the time of theft and report to the Police, assisting in the investigation.
The Associated Press reported in August 2011 that New York City Police Department cars and plate tracking equipment purchased with federal HIDTA funds (High Intensity Drug Trafficking) were used to spy on Muslims in mosques, and to track plates number of worshipers. Police in unmarked cars equipped with electronic plate readers will walk the streets and automatically catalog everyone's plates parked near the mosque, gathering secret databases to be distributed among officers and used for Muslim profiles in public.
In 2013, the American Civil Liberties Union released 26,000 pages of data on ANPR systems obtained from local, state, and federal agencies through freedom of information legislation. "The documents paint a surprising picture of the technology being disseminated with too few rules that serve as a tool for routine tracking and supervision of mass locations" wrote the ACLU. The ACLU reports that in many locations the device is used to store location information on vehicles that are not suspected of certain offenses. "Private companies also use plate readers and share information they collect with police with little or no supervision or privacy protection.Lack of rules means that policies that govern how long our location data is stored varies greatly," the ACLU said. In 2012 the ACLU filed a lawsuit against the Department of Homeland Security, which funded many local and state ANPR programs through grants, after the agency failed to grant access to the requested ACLU records under the Freedom of Information Act of the programs.
In mid-August 2015, in Boston, it was found that the record plate for a million people was online and unprotected.
Inconsistencies and jurisdictional differences
Many claim ANPR claims systems when trained to match plates from one jurisdiction or region, but can fail when trying to recognize the plate from other jurisdictions due to variations in formatting, font, color, layout, and other plate features. Some jurisdictions offer vanity plates or affinity (especially in the US), which can create many variations within one jurisdiction.
From time to time, US states will make significant changes in their plate protocols that will affect the accuracy of OCR. They can add characters or add new plate designs. The ALPR system must adapt to these changes quickly in order to be effective. Another challenge with the ALPR system is that some countries have the same protocol plate. For example, more than one country uses three standard letters followed by four numbers. So every time the ALPR system alarm, it is the user's responsibility to ensure that the plates causing the alarm match the country associated with the license plate listed on the computer in the car. For maximum effectiveness, ANPR systems should be able to recognize the plates of any jurisdiction, and the jurisdiction associated with them, but many of these variables complicate the task.
Currently at least one US ANPR (PlateSmart) provider claims their system has been independently reviewed because it can accurately identify US state jurisdictions from number plates, and one European ANPR provider claims their system can distinguish all EU plate jurisdictions.
Accuracy and measurement of ANPR system performance
Some ANPR software vendors publish accuracy results based on image benchmarks. These results may vary depending on which image the vendor has chosen to include in their tests. In 2017, Sighthound reported 93.6% accuracy on the benchmark personal image. By 2017, OpenALPR reports accuracy rates for their commercial software in the 95-98% range on the benchmark public image. The April 2018 study of the Federal University of Brazil ParanÃÆ'¡ and Federal University of Minas Gerais comparing the two systems reported an average introductory rate of 93.53% and stated a significant increase from the 81.8% level earned in previous employment.
See also
- AI effects
- Artificial intelligence app
- Facial recognition system
- Street polishing unit
- Vehicle location data
- List
- List of emerging technologies
- Outline of Artificial Intelligence
References
Source of the article : Wikipedia
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