Deep LPR/ANPR License Plate Recognition

Automated solutions for parking and traffic management

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.

Case Study

AI-Assisted Computer Vision

Wahtari Automatic Number Plate Recognition (ANPR)

Fast Track Implementation of AI License Plate Recognition


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

The difference of shutter

and why you should use global shutter for industrial image processing and ITS

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.

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 offenses.

Diverse Fields of Application
Automated solutions for parking and traffic management

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 offenses

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

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.

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.

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.

Fast Commissioning
Easy mounting and configuration

Build your own Applications

New features via simple software update

Thanks to the open architecture and the high computing performance, additional functions can be added (docker container) and run in parallel.