Intrada ALPR (ANPR)
Intrada® ALPR (ANPR) is the Q-Free software library solution for Automatic License/Number Plate Recognition (ALPR/ANPR). Intrada® ALPR (ANPR) offers an SDK for reading registration numbers from images. We offer an API for easy integration with C++, C, C# and other .NET applications.
Intrada® ALPR SDK is already used by many OEM partners and integrators worldwide. Applications range from parking, access control and surveillance systems to speed enforcement systems and tolling systems. Reason to choose for Intrada® ALPR is always the combination of accuracy and ease of API integration with the availability of any country module and the ability to run on any regular platform.
Vehicle Analytics feature is an Intrada® ALPR to gather additional identifying vehicle characteristics using the Intrada SDK. Vehicle analytics adds:
- Vehicle Class – Enables operators to charge differently for motorcycles, cars, and buses.
- Vehicle Color – Helps operators and law enforcement easily locate matching vehicles.
- Vehicle Model/Make – Further helps agencies and officers identify lost or suspect vehicles.
- Vehicle Angle – Determines which side of the vehicle is facing the camera, e.g. front of rear, helpful in determining entry and exit points in parking applications.
Licensing and Maintenance
|Model||Long-term contract||Yearly contract||One-off|
|Free SDK Included
|Pricing||Performance-based SLA||Forecast annual volumes||Per camera or recognition|
|Software maintenance||Included||Included||Optional (15% yearly)|
|Supported countries||Over 150 countries and states around the world|
|Countries included||All||All||1 country + generic|
|Hardware locking||None||None||USB dongle|
Application of Intrada® ALPR in tolling back offices typically implies tuning and meeting specific level of identification performance. For such projects we invite you to contact us directly.
|Supported API languages||C, C++, C# and other .NET languages|
|Available bindings||Java, Python|
|Image file formats||JPG (8bit/12bit), TIFF, BMP, PNG|
|Raw image formats (in memory)||8bit grayscale, 8it Bayer (CFA), 12bit grayscale, 24bit RGB, 36bit RGB, YCC 4:2:2, YUV 4:2:0|
|Video formats||MJPEG, H.264, RTSP, RAW frames (in memory)|
*) Support for the ARM family encompasses all regular processor and configuration variants, including the models as installed on the various Raspberry Pi and Pine processor boards.