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Deep LPR/ ANPR

License Plate Recognition.

Automated solutions for
parking and traffic management

An AI-based inspection system can reliably identify license plates regardless of vehicle type, characters, speed and traffic density – even under difficult viewing angles, light and weather conditions.

In addition to number plates, other features can also be identified: vehicle type, road conditions, etc.

ANPR compatible Hardware
ANPR (PDF | 33.148 KB)

Case Study

AI-Assisted Computer Vision
Wahtari Automatic Number Plate Recognition (ANPR)

Fast Track Implementation of AI License Plate Recognition

Read Intel Case Study

Automatic Number Plate Recognition

High End AI system with best
price-performance ratio

Wahtari’s ANPRCam automatically identifies and reads license
plates of approaching vehicles, achieving far better results than
conventional systems. By combining deep learning and edge
computing, the weaknesses of previous ANPR systems have
been eliminated and costs reduced.
The Wahtari ANPRCam therefore not only convinces with a hit
rate of over 99% and ultra-fast detection of 50-100ms, but also
with its good price-performance ratio. Customers also appreciate
the wide range of plug-ins and interfaces, which allows individual
adjustments to the ANPRCam to be made even at a later
stage.

Diverse Fields
of Application

Automated solutions for
parking and traffic management

Typical applications of Wahtari’s ANPR solution include vehicle
access control, e.g., via black & white lists, automatic billing of
e.g., tolls and parking tickets, and free-flow applications in multi-
story car parks or other constellations where RFID transponders
are unsuitable. The ANPR system achieves particularly
high increases in efficiency in scenarios in which a large number
of unknown vehicles are to be identified quickly and without
errors.
The collected data provides an ideal basis for drawing conclusions
about the utilization of the road or parking facility, analyzing
the usage behavior of the drivers and initiating optimization
measures.
Operators of parking facilities, e.g. in sports stadiums and gas
stations, use Wahtari’s ANPR solution to help their visitors
enjoy a smooth stay without waiting times. Used in road traffic,
the ANPRCam monitors up to two lanes to measure traffic density and identify traffic offences.

Automated payment

Time-saving alternative to
parking tickets. E.g. hotel,
corporate parking, car rental.

Automated access control

E.g. shopping center,
hotel, sports stadium,
airport.

Measure traffic density

Determines the current
and average traffic density
and detects traffic jams.

Detect offences

E.g. passing red lights,
service roads, bus lanes,
etc.

Large Selection
of Plug-ins

New features via simple software update

Thanks to the open architecture and the high CPU capacity,
additional functions can be added (even at a later date). In addition
to the a more specific registration of vehicles (e.g. vehicle
type, color), the plugins also support the identification of other
traffic participants (e.g. cyclists). Even plug-ins for the analysis
of the environment can be installed in ANPRCam and are able
to detect the condition of the road (e.g. traffic obstacles, road
damage).

Worldwide
Deployment

All license plate types can be trained and recognized

There are no worldwide unified standards for the design of license plates, which has made the coverage of new regions for ANPR systems very problematic. The compatibility to Wahtari nLab allows a fast and uncomplicated support for new license plate types in many regions. nLab is a fully automated deep learning platform and has already been successfully used for the support of license plates in Europe, as well as in the Arab and Asian regions. Any license plate types and characters can also be supported in retrospective. Any number-plate types and
characters can also be added retrospectively.

Wahtari ANPR Camera

The powerful outdoor camera for the most challenging situations

Wahtari’s ANPRCam automatically detects and reads license plates of approaching vehicles, achieving far better results than conventional systems. By combining deep learning and edge computing, the weaknesses of previous ANPR systems have been eliminated and costs reduced.

Highlights

  • Onboard processing: Evaluation of the license plates within the camera

  • Open architecture: Supports integration of external hardware and software component

  • Extreme high accuracy: Over 99% of license plates are read correctly

  • IT security: protection of data through modern encryption algorithms

  • < 16 watt energy consumption

  • 5-50mm motorized zoom

  • IP66 & IP67 available

Read more about the camera

New AI Approach
solves old Problems

Eliminate weaknesses of standard
vision systems through AI

Detection rate:
The number of incorrectly recognized license plates drops to almost 0 thanks to Deep Learning.

Security and privacy:
The Wahtari ANPRCam is an on-the-edge system: images are processed in the camera and do not have to be transferred
via often insecure cloud connections. Depending on the configuration, images can be deleted immediately after identification.

Visibility conditions:
Based on AI technology, detection is reliable
and accurate even under poor visibility conditions, e.g. due to fog, rain, dirt. This means that no ground personnel has to
be planned in for exceptional situations.

Fast Commissioning

Easy mounting and configuration

The Wahtari ANPRCam can be mounted on existing infrastructure (e.g. traffic lights, street lamp), on its own pole or on walls.

After installation, only the angle of view, zoom and focus need to be adjusted, which requires a one-time connection to the camera. The uncomplicated commissioning requires hardly any technical know-how.