We transform your cameras into intelligent machines capable of identifying license plates of passing vehicles.

The License Plate Recognition (LPR) feature allows you to identify license plates on passing vehicles using video streams from your cameras. The recognized plates are then stored in a database, allowing you to create smart alerts and automations based on LPR events. Each record includes the time and date of recognition, license plate number, confidence level, camera ID, and links to the corresponding video archive files. This valuable information enables users to efficiently review and access specific footage through our user-friendly portal.

To achieve reliable License Plate recognition, it is required to properly place and configure the camera, enable and adjust appropriate event detection on the camera. Any of the camera modules that generate events can be used and the best option (simple motion detection, line crossing, intrusion, etc.) will depend on the specific scene conditions and camera positioning.

NOTE1: Cloud object detection has to be enabled for the camera and vehicle object type selected in order for the license plate recognition to work.

NOTE2: The license plate must be visible to the camera for more than 1 second. If the car is passing in front of the camera faster, the plates won't be recognized.

Almost any modern camera can be used for LPR, though the best results will be achieved with models that allow you to control image settings such as shutter speed, frame rate, and bit rate manually or semi-automatically (when you can set a range of minimum and maximum parameters for the camera). Additionally, the combination of lens and resolution should be chosen to ensure that the captured license plate has a minimum width of 100 pixels. For example, even a 720p camera can be suitable when paired with a narrow lens, whereas a 4K fisheye camera positioned 15 meters away would not provide sufficient clarity.

When considering camera placement for license plate recognition, it is recommended to install them at entrance checkpoints or driveways where vehicles are required to pass in front of the camera. For optimal visibility of license plates, position the cameras at road level or at a slight angle above the typical height of a car. It is important to ensure that the typical path of vehicles driving near the camera directs them toward or from the lens, encouraging direct engagement with the camera, even if only for a brief moment. Depending on the laws in your area, the front license plate might not be required, and in such a case, the camera should be positioned in such a manner that it is guaranteed to capture the rear of the vehicle. This positioning maximizes the chances of capturing clear and readable license plate images.

In the above example, the camera is positioned well, it is positioned just slightly above the car height level, and cars are coming in and out of the parking area

A car's License Plate must be adequately illuminated, preventing over or underexposure to the picture. Avoid areas where the car's Plate will be illuminated by direct sunlight, or scenes with high contrast, like indoor parking near big windows, or long corridors with one light source at one end, places with constant changes in illumination due to automatic lights, or upon garage door opening. Uniform and constant illumination of the Plates to be recognized is required for reliable recognition. Avoid bright spotlight sources this will create sharp shadows. Diffused and soft light sources are recommended.

If the camera has to be installed against the light source, a bright object on the background (for example, the sun behind the entrance), the camera exposure (or brightness) should be set to be above the default (automatic) value, overexposing the background to ensure that the plate in the frame becomes lighter and the text is readable.

Also note that some features of the cameras (WDR, Backlight compensation, Highlight compensation, etc.) typically result in blurry frames. Check how these features influence the final image quality, specifically how sharp and contrasting the moving vehicle is. It is better to have under / overexposed areas in the image with sharp license plate text than even lighting but a blurry plate.

The camera resolution and the lens must ensure that the car's plate is at least 100 pixels across when passing under the camera, for a more reliable recognition, 150+ pixels is recommended. For low-resolution cameras, this means that the car must pass closer to the camera, or a zoom lens must be used.

The recommended camera frame rate is between 8 and 15 fps(frames per second) for slow-moving vehicles, but must be increased to compensate for speed if the recognition is required over a road with high-speed limits. The rule of thumb is that the plate should be visible on at least 5 frames.

The camera must have the capability of exposure adjustment to avoid getting blurry images of passing cars. The minimum shutter speed should be limited to 1/100 at most; recommended is 1/150 of a second or faster. The priority between the shutter speed and the aperture must be given to the shutter speed; in some models, this is controlled by the sharpness/smoothness settings. Sharpness should be given priority. This means that it is preferable to get a darker image than a blurred one. Depending on the camera manufacturer, this setting can be called “Allow low shutter” or the limitation of the “maximum exposure” set this to 1/100 or less. The cameras without this capability will result in a blurry image that may look better in motion, but the stop-frames will be blurry, decreasing the accuracy of plate recognition or even making it impossible to recognize a license plate. The increased sharpness on the camera leads to significant visual noise, which results in false triggering of the motion detector. To avoid this, provide better illumination at the camera location.

Note: Usage of the H.264 codec with high compression or a large interval between the keyframes may lead to the “tailing effect” of the moving objects in the resulting image. To overcome this, set a higher bitrate in the camera settings and reduce the interval between the keyframes.