The Scale-invariant Feature Transform(SIFT) algorithm was improved in this paper, which could match two pictures and could also compute the object rotation angles in the pictures. Firstly, the SIFT was used to extract two images according to the SIFT feature invariance. Then, the computing process for the main direction of the feature point was analyzed, and the main angle for every key point was recorded. After matching two pictures, the angle difference of main direction for each pair of matched SIFT feature points was calculated and the rotation angle of feature point was obtained. Afterthat, all of the rotation angles of the feature points were analyzed by iterative self-organizing clustering method. Finally, the correct class of samples was selected by the variance and the number of samples within the classe, and the mean of the correct class was used as the final rotation angle of the object. The experiment results indicate that the rotation angle error is within 3° when the image distortion is not significant and it can also well estimate the rotation angle even if the object is partially occluded. Furthermore, in the case of the time complexity does not increase obvionsly, the SIFT can compute the rotation angle of the object, which expands its applications.