you can change thresholds when you find extremums in DOG images or find difference between extermum and mean value of window( window which consists of 28 neighbor's pixel value(see sift algorithm details)) and save them to find stronger points. The greater difference value, the stronger key point.

Dear Hossein,

Do you have Matlab code for it?

1.Read an image

2. Extract the sift descriptor and store it in some variable name such as siftpoints and then add this code

figure;

imshow(Image);

title('100 Strongest Feature Points from Image');

hold on;

plot(selectStrongest(scenePoints, 100));

selectStrongest is an inbuilt function in matlab 2014b

try this link to see what I had pointed above:

http://www.mathworks.com/matlabcentral/fileexchange/46118-sift-key-point-detector-in-matlab?s_cid=srchtitle

I think that your questions was answerer by Hossein and Sameer. But if you have more questions I could help you.

Thanks. That's OK.

hi, I store SIFT Feauters in some variable name such as siftpoints but selectStrongest(scenePoints, 100) function select strongest with metric properties but sift features don't have metric properties