Matching features points of rotate image using SURF
SURF Features are not completely rotation invariant. 

In the paper, they try to make SURF more robust to rotations by following the following methodology.

In order to improve the performance for rotation, the descriptors are based on multi-orientations. The many-to-many tentative correspondences are determined with a maximum distance. Hough transform is used to reject the mismatches and the affine parameters are computed with a least-squares solution.

The image matching algorithm shows a better performance for image rotation than the standard SURF and it succeeds in matching the image including repetitive patterns which will deteriorate the distinctiveness of feature descriptors.