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License Plate Detection Events

Flussonic can detect license plates and recognize car numbers on the video transmitted by an IP camera including non-standard format numbers. This functionality is known as ANPR (automatic number plate recognition).

Flussonic does the following:

  • Creates events of license plate detection. Video comes from IP cameras to a streamer (in cluster mode) or to the managing server (in single mode), where the number recognition takes place.

  • Provides the Watcher UI for viewing plate detection events. You can view registered events and watch the recorded video of each event.

  • Provides the API for integration with external services.

Number recognition is available for the following countries:

  • Hungary
  • Czech Republic
  • Moldova
  • Russia
  • Abkhazia
  • Ukraine
  • Armenia

To start detecting car numbers:

  1. Prepare hardware and software for the Flussonic server that will carry out number recognition — see Video analytics module installation.

  2. Check the video image parameters for compliance with the recommendations (see below).

  3. Turn on and configure the car number recognition. To configure the feature, use the web interface or the configuration file, but please remember that some options can be set only through the file.

On this page:

A general requirement for a video image for ANPR is the ability to read the license number plate with human eyes. In other words, if you do not perceive the number in the video, then Watcher will not be able to recognize it either.

Stable ANPR is guaranteed with the following video image characteristics:

  1. At least HD resolution (1280 x 720).
  2. The size of the license plate in the image at least 100 x 20 pixels.
  3. Good illumination.
  4. Colored image is better than black-and-white.
  5. Any camera view angle.

However, if your video image does not meet these guidelines or even if your country is not supported yet, you can check to see if recognition will work. If the ANPR quality turns out to be unsatisfactory, we may consider the module modification to suit your conditions. Please contact our technical support team by following these instructions. Technical support team member will request the necessary information and will let you know if the improvements are possible and when we will implement them.

Please note that if your country is already on the list, then access to video stream(s) where the recognition quality does not meet expectations is enough. If you want us to support the license number plates recognition for a new country, then most likely you will be asked to provide access to two types of streams:

  • The camera is aimed at the number at a right angle (90°)
  • The camera is aimed at the number at an arbitrary angle
Example right angle
Example arbitrary angle

Technical support team member will provide a detailed info at your request.

Setting up ANPR in the configuration file


You can do the same through the Watcher UI – the settings will be saved to the config file automatically. But you will still need to check the GPU number in the file and edit it, if necessary.

  1. Open the file /etc/flussonic/flussonic.conf.
  2. Add the line plugin vision;, which enables the recognition system.
  3. Add the vision directive to a stream's settings, and specify the GPU number:
stream cam1 {
  url rtsp://;
  vision gpu=0;

stream cam2 {
  url rtsp://;
  vision gpu=1;

plugin vision;
  • gpu (required) – GPU number. You can use the nvidia-smi tool to find out which number is assigned to your GPU.

Reload the configuration with service flussonic reload so that the changes made to the file take effect.

Setting up ANPR in the UI


Before you configure cameras in the UI, make sure you enable the recognition system. Add the line plugin vision; to the configuration file /etc/flussonic/flussonic.conf.

Enabling license number recognition


The recognition settings may not be available if you have selected a non-adjustable preset.

To turn on plate detection and number recognition for a camera:

  1. In the Watcher UI, go to Cameras. Find the camera in the list and open its settings by clicking the icon in the upper right corner of the player.

  2. Check the Enable recognition box.


  3. Select Recognize license plates in the drop-down list that appears when you check the box.

  4. Select the period to store precise thumbnails for, if necessary. Please refer to Camera settings for details on precise thumbnails.

  5. By default, the recognition system searches for car numbers over all the camera field of view. You can select specific area(s) to detect numbers in by clicking Set up the detection zone. This settings may help you to reduce false detections.



    The recognition settings may not be available if a non-adjustable preset is selected. In this case, select or create the preset with the settings you need.

Now Flussonic will recognize car numbers that appear in the frame of this camera, and mark the time when the car entered and left the scene. Flussonic modifies the stream settings in the configuration file /etc/flussonic/flussonic.conf.

You may need to edit the GPU number manually in the configuration file (see the previous section for details about setting up ANPR in the configuration file).

Viewing ANPR events in Watcher

Flussonic creates events of two types:

  • enter – a car number appeared in the field of view of a camera
  • leave – a car number left the field of view.

To see detected car numbers for a camera:

  1. In the Watcher UI, go to Notifications. The list of all events opens.
  2. You can use filter to find specific events:


    • In Camera, enter the camera name.
    • In From and To, select the date and time of beginning and end of the period when events were detected.
    • In Search, type the car number.
    • To delete the specified search criteria, click Clear Filter.
  3. The list of events is filtered as you enter search parameters.

  4. Click the event to view its recording. The player will appear on the bottom right to play the recording. To enlarge the player, just double-click it.