Graph Based Image Segementation using k-means alogorithm and normalised cuts
$10-30 USD
Paid on delivery
In Image segmentation using N-Cuts algorithm, the image is modelled as a graph,
where each Node of the graph is a pixel of the Image. And the nodes are connected by
weighted edges. The weights are determined by the similarity between two pixels. N cuts
algorithm tries to find an optimum partition of Image into N segments. Since Images have
1000s of pixels solving such graphs is a computationally tough task. Hence a simplified
algorithm is required to apply N-cut in real time. So the images are divided into cell to reduce the computational complexity and the segmentation is being carried out in two stages.
Project ID: #10242216
About the project
7 freelancers are bidding on average $112 for this job
Wonderful Project! We are pro in Matlab... As we are masters of mathematics and control engineering, we will give a successful result in time. Plz keep in touch with me! Thanks..
NO PROBLEM...................................................... JUST PING ME.................................................... THANKS
I have already a written code of k means which compresses the colours. I have also applied the same using PCA algorithm which gives faster and more precise result. If you are interested please let me know in 3 days as More
Using graph cuts we will first perform image segmentation and then use k -means algorithm to improve speed and accuracy. We will be able to write the algorithm and generate the results
