- OCR software for license plate reading
- Worldwide coverage
- Industry-praised accuracy
- Independent from image source
Carmen® powered ANPR Cloud SaaS
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ANPR (Automatic Number Plate Recognition), LPR (License Plate Recognition), or ALPR (Automatic License Plate Recognition): they all stand for an image processing software that is capable of recognizing license plates and transforming them into digital data.
ANPR or LPR? For further reading about the terminology, we suggest checking this blog article.
The operation of any ANPR system is comprised of three main elements.
At the front end of any ANPR system, a camera captures images of the license plates. The camera is important as it needs to capture images that are optimal for ANPR purposes. This is crucial for the overall performance of the system. The best ANPR results are achieved by using cameras designed especially for ANPR.
Adaptive Recognition offers a wide range of such specialized ANPR cameras.
ANPR systems read the plate text and identify the plate type from a preselected set of captured images.
Automated recognition involves several steps like image normalization and enhancement, detecting the vehicle in the image, then finding the plate on the image. The final step is done by the OCR (Optical Character Recognition) algorithm that recognizes the individual characters and transforms them into digital text data.
For more information about image preselection and triggering, download our free e-book.
Besides the individual characters and the type of the vehicle plate, the CARMEN® ANPR also returns plenty of additional information, such as an image with the recognized plate(s), and the confidence level assigned to each character and a confidence level for the whole plate. The result also includes the nationality and the color of the plate (in selected regions/counties), with time-stamp and optionally geographical coordinates.
Once all license plate data have been saved to a database, the data record serves as input to the end user’s business logic. Automatic number plate recognition may be a key component of vehicle access control, traffic and toll enforcement and many other areas.
ANPR accuracy depends on two major factors:
Higher quality input means a higher chance of 100% accuracy. In general, if an image is hard to recognize for humans, it will be similarly hard to recognize for an ANPR system. The license plate on the captured images should not be too distorted, blurred, or over-exposed. For this, we offer a complete guideline in our 24/7 ANPR image guide.
ANPR can be used in any road traffic environment from parking houses to highways, with a wide range of benefits.
Access control systems use it for a license plate-based entry/exit control. Modern highways use ANPR for automated toll control. Traffic management systems use license plate recognition for identifying wanted vehicles, detecting speeders and violators. ANPR is used for congestion charging, journey time measurement (JTMS), and more in smart cities.
When checking ANPR software options, the following factors should be considered:
Depending on these factors, Carmen® offers ANPR software versions for 1-core, 2-core, and 4-core CPU processing and various engines for local, regional and even global geographics (on Cloud).
With today’s contemporary deep learning technologies, ITS systems detect the category, weight, or license plate and the brand, model and color of the passing vehicles. Linking ANPR with make, model and color data is particularly important when detecting replaced or stolen license plates.