A region duplication image forgery detection algorithm based on Harris feature points and annular average representation is proposed. Firstly, an adaptive Wiener filter is applied to the image, and then Harris operator is utilized to extract feature points in the image. Secondly, a feature vector matrix is constructed with average values of pixels to make a quantity description of annular neig hborhood around each feature point, and lexicographical sorting and threshold processing are employed to implement similarity matching with the purpose of determining the candidate matching points. Finally, random sample consensus (RANSAC) algorithm is used to eliminate the erroneous matching points, and then the duplicated and tampered regions are located with identifiers. Experimental results show that the proposed algorithm is robust to rotation and flipping transformation of the copied region, and it can effectively resist common post-processing attacks such as Gaussian blurring, AWGN, JPEG compression and their mixed operations, especially the copy-move forgery with flat area of little visual structures and small area.