Color image segmentation based on K-means clustering using LabVIEW Machine Learning Toolkit

[Klemen]

Hello everybody,

this post is a Labview code example on how perform image segmentation using the K-means clustering algorithm from the Labview Machine Learning Toolkit. This excellent and useful toolkit can be found here:

https://decibel.ni.com/content/docs/DOC-19328

I have used the Matlab example as a reference for the segmentation, which can be found here:

http://www.mathworks.com/help/images/examples/color-based-segmentation-using-k-means-clustering.html

The objects in the image were separated into three clusters. The results for Matlab and Labview implementation are shown below.

                                Matlab                                                           Labview

 

 

 

Some variation can be seen between the examples, so some further testing needs to be performed in order to pinpoint the discrepancies. But in any case, fairly good segmentation results can be achieved. Below are some examples:

or the background:

The Labview code is in the attachment (saved for Labview 2013). Eventhough my contribution is not great (majority of the credit goes to the Labview Machine Learning Toolkit), I hope this helps someone somewhere along the way...

Best regards,

K