CARMEN ANPR SOFTWARE
License plate recognition for applications where accuracy matters
Digifeat deals with CARMEN ANPR(Automatic Number Plate Recognition) SOFTWARE in Dubai. Carmen Anpr Software is an Automatic Number Plate Recognition software that reads all vehicle plate types in the world – at any traffic speed. Toll collection and congestion charging systems, traffic monitoring and security, speed and journey time measurement, bus lane and traffic light enforcement, parking or access control and many other systems benefit from the fast, exact, automatic identification and recognition capabilities of this ANPR software – since the 1990s, when the solution was first created – and constantly fine-tuned ever since.
✓ Worldwide express shipping
✓ Unmatched customer support
The Carmen® ANPR software reads license plates from many image sources remarkably fast and with the highest recognition accuracy in its class. It offers country-independent recognition of not only Latin characters, but also Arabic, Cyrillic, Chinese, Korean, Thai and many more, as well as reflective, non-reflective, personalized and special interest plates that are typical in many U.S. states.
DESIGN YOUR ANPR SYSTEM EASILY WITH CARMEN
We know that license plate recognition projects are complex – so designed our system to be flexible and we offer multiple versions to adapt to your project needs.
PARKING, CITY OR HIGHWAY
The FreeFlow version offers unlimited capacity while the K version is designed for other, low/medium frequency applications for cost-efficiency. Consult with our sales experts to find out which version is the best for your project.
GEOGRAPHICAL COVERAGE
In your ANPR project, you might need to capture only local license plates, or have a global coverage – or maybe some part of it. Carmen® offers various geographic ANPR engines to make sure it fits your project.
PROCESSING OPTIONS
Carmen® is available in single, dual and quad-core processing capabilities, with easy upgrade options. Plan your system workload using the flexibility of this ANPR.