Greetings to the members of the community!
I am trying to segment a grayscale image of size m-by-n using k-means clustering ( k = 3, in this case). In this attempt, I am using the normalized values of the pixel coordinates and intensity levels as the coordinates in the feature space to perform k-means clustering.
For e.g. for a pixel located at (x,y) having an intensity of I(x,y) the coordinate of that data point in the feature space is (x/m, y/n, I(x,y)/max(image))
Once the clustering is completed that is the centroid values of the clusters no longer change their coordinates drastically (checked by setting a threshold value) from their positon in the previous iteration, the pixels corresponding to the data points are re-allocated with a new intensity value.
However, when I run the program, the overlayed image doesn't match that obtained from using the in-built function imsegkmeans.The attached code is specific to k = 3. I am not able to figure out what piece I am missing or doing incorrectly.
Please share your valuable suggestions on how do I perform the clustering operation correctly.
Thanks!
