Convergence of SIFT points

The convergence of the key points to the converged Synapses can be understood from the below graphs. In the first set of graphs shows the histograms of distances between SIFT points and ground truth synapses points when the weighing function is a Gaussian (weighed most on the centroid).


The next graph shows the distance histogram when the weighing function is equal on all pixels on the circular patch.

The plot of SIFT key points generated over a Perona Malik method smoothened image is shown as below.

The points are really close to one another. Probably we can run a clustering algorithm (here and here) that will decrease the number of SIFT key points to be analyzed. This will also help in making the kNN classification algorithm faster.