The thesis investigates features on detecting copy-move duplicated regions. The structure of copy-move detection is searching keypoints through the Scale Invariant Feature Transform(SIFT), matched blocks acquired from these keypoints by invariant moments, region growing by surrounding matched blocks. The analyses include the Scale Invariant Feature Transform(SIFT) for calculating keypoints, keypoints match, invariant moments comparisons, sizes of region growing blocks. This thesis examines various parameters and thresholds of the adopted structure. We also find that there are many factors to affect the detected results. Three conclusions are summarized. First, Hu’s invariant moments are better than Zernike invariant moments. Second, positions of duplicated regions can be acquired from keypoints through a robust neighboring search. Third, the optimal growing block size is then acquired. At last, a set of optimal parameters are found through the exhausted experimental results.