This article describes the first 5 steps to install your new Daheng machine vision camera on a Windows machine. For different operating systems, please check out the manuals on our Download Page or our installation guides for Linux, Raspberry Pi, etc.
**Please don’t connect your camera until after the installation process**
Download the SDK for our machine vision cameras from our download page.
Unpack the zip and execute the .exe inside.
When asked which drivers to install, please select the necessary ones. If you are unsure, select all of them. You can also install or uninstall these drivers later on.
Once correctly installed, you can find programming samples and documentation in the installation directory. In addition, you can find the utility programs Galaxy Viewer or the GigE IP Configurator in the Galaxy Devices folder in the windows start menu.
The camera can now be connected to the PC.
If you are using a GigE camera, make sure that the camera has sufficient power before setting the IP address using the GigE IP Configurator.
Now you can connect the camera in the Galaxy Viewer by double clicking the camera name. By pressing the play button, you can start the image stream.
If you experience issues with connecting your GigE camera, please make sure that you changed the necessary firewall settings.
- Open Windows Defender Security Center.
- Click on Firewall & network protection.
- Click the Allow an app through firewall link. ...
- Click the Change settings button.
- Check that both GalaxyView.exe and GxGigeIPConfig Applications have access to private and Public network
If you are using a USB3 camera, the above-mentioned steps are not necessary. It will be displayed in Galaxy Viewer right away. In addition, you can find it in the Windows Device Manager as Machine Vision Device.
Please note: the majority of USB3 cameras are powered by the USB3 connection. Insufficient power supply from the USB-port may lead to malfunction. In that case, try another port or test with a different computer. Some USB3 cameras have a high power consumption and will be powered by the I/O-cable.
There is a chance that the first acquired image you see is too dark. Therefore, we first have to set up the exposure time of the Machine Vision Camera. Also, make sure you have the correct lens mounted to the camera (see Lenscalculator) and the aperture is opened.
If you just want to get familiar with the machine vision camera, we advise to point to a light source like your computer screen. If the camera is built into the final product, please make sure that the ambient lighting of the final product is being used.
There are 2 options to proceed:
This is the most easy option. Therefore set the ExposureAuto feature to Once or continuous. (Under: Remote device>Acquisition control>ExposureAuto)
(Under: Remote device>Acquisition control>ExposureTime)
Please note that the exposure time is in µs. So 40000µs = 40ms. By increasing the exposure time the image will get brighter, but it can influence the framerate and cause motion blur.
The maximum achievable framerate of the Machine Vision Camera is 1000/exposure time (ms). With an exposure time of 40ms, the max. framerate is 1000/40=25fps. If you are imaging a still object, please increase the exposure time till you have the desired brightness.
For moving objects, the exposure time of the Machine Vision Camera is critical. If the exposure time is too long, the image will get blurry.
A common calculation states that the maximum movement of the object should not be larger than half a pixel. To calculate, we assume the following: Our field of view is 1000x600mm and our Machine Vision Camera has 1000x600pixels resolution. So 1pixel/1mm. If an object moves with 1m/second, this will be 1000mm/second. We will start noticing motion blur if the object moves with more than half a pixel; that is 0,5 * 1pixel/1mm= 0.5mm. The maximum exposure time is: (max object movement=0.5mm) / (object speed = 1000mm) = 0.0005seconds = 0.5ms. In our calculation, we would set the parameter ExposureTime of the Machine Vision camera to 0.5x1000=500µs
When using one (or more) ethernet GigE camera and you don't have live images, the packets size and packets delay can be the problem. Sometimes you can encounter issues such as frames overlapping, so the previous image is partially over-imposed on the new one. From programming software you may see errors such as failed to get image, getting image failed, incomplete frame.
Please optimize the parameters GevSCPSPacketSize and GevSCPD by slowly increasing the values until you receive live images or no longer have problems with image. Standard values for initial testing are GevSCPSPacketSize=8192 and GevSCPD=1000.
In the Galaxy Software you will find these parameters at Remote Device -> TransportLayerControl or via the searchbar:
In Python you can set the values by adding these lines:
cam.GevSCPSPacketSize.set(8192)
cam.GevSCPD.set(1000)
**(8192/1000 are sample values)
When using multiple camera you need to change the GevSCPS and GevSCPD to specific values, please refer to this page (bottom): Frame rate calculator
See also our article about connecting multiple GigE cameras to one ethernet-port.
A color Machine Vision Camera has a white calibration option. Color representation of a Machine vision camera is depending on the light source that is used. LED’s have a different color spectrum then a traditional light bulb or the sun. Often the image looks very green if the white balance is not correct. Therefore, set the BalanceWhiteAuto feature to once or continuous. (Under RemoteDevice -> AnalogControl -> BalanceWhiteAuto)
As soon as the white balance is performed, you will notice that the colors of the Machine Vision Camera are more realistic.
Learn more about this in our article on exposure time, white balance and color correction.
Now that you can acquire high quality images, you might want to have a look at more advanced functionalities of your camera.
If you can’t find your answers in our Knowledge Center, feel free to contact us:
