Based on AI algorithm, the LPR function provides value-added data via a pre-trained deep learning model and continuously training to algorithms automatically, which can not only recognize vehicle plates in real time with high accuracy, but also identify more vehicle features, like vehicle type, color, etc., generating powerful security and traffic insights.
License Plate Recognition (LPR/ANPR) is a technology that uses optical character recognition on images to read vehicle registration plates to create vehicle location data. It can automatically recognize vehicle license plate’s number and other related information using the technology of license plate position tracking, character segmentation and character recognition.
Milesight LPR/ANPR is embedded in Milesight Network Cameras. It automatically detects and captures license plate in real time and compares to a predefined list, then takes appropriate action such as generating an alert once the license plate is on the predefined blacklist.
With built-in intelligent video analysis, Milesight LPR/ANR Network Cameras have the ability to detect and recognize the moving vehicle's plate number in the speed up to 200km/h. And the recognition accuracy is more than 95%. Also, Milesight LPR/ANPR Network Cameras could be compliant with CGI and other third-party VMS.
Milesight LPR/ANPR Network Cameras are perfectly useful for traffic solutions. The cameras detect and catch the vehicles’ plate numbers. Then there will be log records which could also be exported. Embedded with Black and White list inside the cameras, control the barrier opened by the camera according to the B/W list achieves a great stand alone solution. Therefore, it is ideal for LPR applications such as traffic surveillance, car parking and entrance & exit license plate recognition.
Milesight LPR is now available in various countries and regions including Mid-East, Africa, Asia-Pacific, America, Europe, Russian-speaking countries.
|Japan||Russian Federation||Saudi Arabia|
|United Kingdom||United States||....|
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