Outline steps needed to minimize these challenges

Next Page content If an organization is considering whether to collect data on its own or get help from an external consultant, it will need to have enough information to make an informed decision about how to proceed.

Outline steps needed to minimize these challenges

Early trial systems were deployed on the A1 road and at the Dartford Tunnel. The first arrest through detection of a stolen car was made in The collection of ANPR data for future use i.

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 alphanumerics of the license plate.

ANPR systems are generally deployed in one of two basic approaches: When done at the lane site, the information captured of the plate alphanumeric, date-time, lane identification, and any other information required is completed in approximately milliseconds [citation needed].

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[ edit ] The font on Dutch plates was changed to improve plate recognition. When Dutch vehicle registration plates switched to a different style inone of the changes made was to the fontintroducing 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 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 be 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.

During the s, significant advances in technology took automatic number plate recognition ANPR systems from limited expensive, hard to set up, fixed based applications to simple "point and shoot" mobile ones.

This was made possible by the creation of software that ran on cheaper PC based, non-specialist hardware that also no longer needed to be given the pre-defined angles, direction, size and speed in which the plates would be passing the camera's field of view. Further scaled-down components at more cost-effective price points led to a record number of deployments by law enforcement agencies around the world.

Smaller cameras with the ability to read license plates at higher speeds, along with smaller, more durable processors that fit in the trunks of police vehicles, allowed law enforcement officers to patrol daily with the benefit of license plate reading in real time, when they can interdict immediately.

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Despite their effectiveness, there are noteworthy challenges related with mobile ANPRs. This equipment must also be very efficient since the power source is the vehicle battery, and equipment must be small to minimize the space it requires.

Relative speed is only one issue that affects the camera's ability to actually read a license plate. Algorithms must be able to compensate for all the variables that can affect the ANPR's ability to produce an accurate read, such as time of day, weather and angles between the cameras and the license plates.

A system's illumination wavelengths can also have a direct impact on the resolution and accuracy of a read in these conditions.

Outline steps needed to minimize these challenges

Installing ANPR cameras on law enforcement vehicles requires careful consideration of the juxtaposition of the cameras to the license plates they are to read. Using the right number of cameras and positioning them accurately for optimal results can prove challenging, given the various missions and environments at hand.

Highway patrol requires forward-looking cameras that span multiple lanes and are able to read license plates at very high speeds. City patrol needs shorter range, lower focal length cameras for capturing plates on parked cars.

Parking lots with perpendicularly parked cars often require a specialized camera with a very short focal length. Most technically advanced systems are flexible and can be configured with a number of cameras ranging from one to four which can easily be repositioned as needed.

States with rear-only license plates have an additional challenge since a forward-looking camera is ineffective with oncoming traffic.

Outline steps needed to minimize these challenges

In this case one camera may be turned backwards. Algorithms[ edit ] Steps 2, 3 and 4:The Online Writing Lab (OWL) at Purdue University houses writing resources and instructional material, and we provide these as a free service of the Writing Lab at Purdue.

If an organization is considering whether to collect data on its own or get help from an external consultant, it will need to have enough information to make an informed decision about how to proceed.

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