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To configure License plate recognition (IV), do as follows:

1. Download Addon IV LPR from the website and install it.

2. Submit Submit to the technical support the MAC address of the Server on which the license should be activated to your Axxon Soft manager. In return, the manager will provide you with a license file.where the detection tool will be used.

   Note
   title Attention!
   The detection tool will not operate on a the Server having with a different MAC address.

   
   

3. Copy an IV license into the license received from technical support into the C:\Program Files\Common Files\AxxonSoft\DetectorPack\LicenseFile_LprIV.txt file.

4. Restart the Server (see Shutting down a Server, Starting a Server).

5. Select the Create the License plate recognition (IV) object (1) object and select it.
   

6. If you require using need to use this detection tool for real-time number license plate recognition (see , set the corresponding parameter to Yes (1, seeConfiguring online Vehicle License Plate recognition), set the corresponding parameter to Yes (2).

7. If you need to enable recording of record metadata, select select Yes from the Record objects tracking list (32).
8. If a the camera supports multistreaming, select the stream for which detection is needed (3). Selecting a low-quality video stream allows reducing the load on the Server (4)..

9. Select the Algorithm for detecting vehicle direction (1):

   1. By LP coordinates: if LP coordinates change position from top to bottom, the vehicle moves towards the camera. If LP coordinates change position from bottom to top, the vehicle moves away from the camera.
   2. By LP scale change: if LP scale increases, the vehicle moves towards the camera. If LP scale decreases, the vehicle moves away from the camera. 
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10. Select the country from the list (1).
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    Note

    title	Attention!

    Several profiles are provided for India, USA, Russia, Taiwan, Australia and African countries, differing by recognition parameters and hardware requirements.

    for LPR and the level of recognition accuracy (2).

    1. High CPU load, high recognition accuracy − provides the maximum recognition accuracy, but creates a high load on the CPU and/or GPU.

    2. Medium CPU load, medium recognition accuracy − provides a high recognition accuracy, requires less computing resources than the maximum accuracy.

    3. Low CPU load, low recognition accuracy − provides the fastest recognition speed, but the recognition accuracy is low

    To recognize US license plates with vertical orientation of characters, a profile with higher accuracy of recognition is recommended

    1. .

11. Select a processing resource for decoding video streams (23). When you select a GPU, a stand-alone graphics card takes priority (when decoding with NVidia NVIDIA NVDEC chips). If there 's is no appropriate GPU, the decoding will use the Intel Quick Sync Video technology. Otherwise, CPU resources will be used for decoding.
12. Specify the minimum number of processed frames per second during recognition (4).

13. Analyzed By default, the analyzed framed are scaled down to a specified resolution (34, 1920 pixels on the longer side). This is how it works:

    1. If the longer side of the source image exceeds the value specified in the Frame size change field, it is divided by two.

    2. If the resulting resolution falls below the specified value, it is used further.

    3. If the resulting resolution still exceeds the specified limit, it is divided by two, etc.

       Info
       title Note
       For example, the source image resolution is 2048*1536, and the limit specified value is set to 1000. In this case, the source resolution will be divided halved two times (down to 512*384): , as after the first division, the number of pixels on the longer side exceeds the limit (1024 > 1000).

       
       

       Info
       title Note
       If detection is performed on a higher resolution stream and detection errors occur, it is recommended to reduce the compression.

       
       

14. Set the number of frames processed per second by the detection tool (5). The value should be in the range [0,016; 100].
15. Set Specify the maximum number of processor cores available for the detectordetection tool. 'The 0' value means that all cores are used (5)6). The value should be in the range [−1; 1].
16. Set the maximum and minimum width of the vehicle number license plate as a percentage of the FoV frame width (67, 7) 8). The value should be in the range [1; 100].
17. Set minimum quality of ANPR LPR (89). The higher the minimum recognition quality, the less fewer false detections positives will occur.
18. By default, CPU resources are solely used for recognition. If you want to apply GPU computing resources to increase the recognition performance, select GPU in the Processing unit field (9).
19. Specify the maximum and minimum number of digits in the number (1, 2).
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20. Select recognition accuracy (3): 

    1. maximum: offers maximum recognition accuracy at the expense of higher CPU/GPU load;

    2. high: offers acceptable recognition accuracy for less CPU/GPU effort;

    3. fast: offers fastest recognition speed at the expense of accuracy.

21. be detected. The value should be in the range [0; 100].

22. Select the processor for the detection tool − the CPU or one of NVIDIA GPUs (10,see General Information on Configuring Detection).
    

    Note
    title Attention!
    It may take several minutes to launch the algorithm on NVIDIA GPU. You can use caching to speed up future launches (see Configuring the acceleration of GPU-based neuroanalytics).

    
    

    Info
    title Note
    If there are several GPUs in the system, a specific NVIDIA GPU value can be assigned to each License plate recognition (IV) tool.

    
    

23. In the Event timeout field (1) specify the time interval in seconds between the initial LP recognition and event registration. The value should be in the range [0; 3600]. The 0 Specify the time interval between the initial recognition and event registration in the Timeout field (4). Zero value sets the event registration to the moment when the track disappears from FoVFOV.
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24. Specify the maximum and minimum number of characters in LP (2, 3). The value should be in the range [1; 20].

25. In the Tracker timeout

    . sec

    field (4), enter a time period in seconds after which the vehicle track is considered lost. The value should be in the range [0; 3600].
    

    Info
    title Note
    This parameter should be used to prevent double detections that occur, for example, when the LP is recognized in the

    time before detection starts again after a number plate is recognized (5).

    frame then gets hidden behind a visual obstacle and after that gets recognized by the detection tool again. If you set the timeout longer than the time of possible LP overlapping in the frame, the detection tool will trigger only once.

    
    

26. You can configure the LPR area in the FOV. The area You can configure an ANPR zone in FoV. The zone is resized by moving the anchor points Image Removed Image Added. 
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    Info
    title Note
    For your convenience, you can click the button and configure the mask on a still frame/snapshot. To undo, click this button again.

    
    

    Info
    title Note
    Detection zone area is displayed by default. You can click the button to hide the zonearea. To undo, click this button again.

    
    

27. Click the Apply button.

Configuration of  of License plate recognition (IV) is now complete.