I have come up with a new descriptor(floating point). I want to evaluate this descriptor against SIFT, GLOH, etc etc. I am using the K. Mikolajczyk, C. Schmid, approach. The method is described in the link http://www.robots.ox.ac.uk/~vgg/research/affine/descriptors.html. They have provided the binaries and the data set. I extract the patches(41x41) and apply my descriptor on these patches. But the problem is, these patches are not rotational normalized.
SIFT achieves rotation in-variance by rotating the patch in the direction of the dominant angle of the patch. My query is ,how to rotate the patch or achieve rotation normalization? I want the original patch(41x41) and the rotated patch to have the same dimension (41x41). For example, If i use the matlab function imrotate and rotate the original patch by 60 degrees. The rotated patch has a dimension bigger than (41x41). And there are blank spaces in the border of the rotated image. I think applying my descriptor on these rotated and enlarged patches gives wrong results.
M question is, How do i rotate the patches or rotational normalize the patch(Such that the original patch and the rotated patch have the same size 41x41) to apply my descriptor?