Image Multiple Copy-move Forgery Detection Algorithm Based on Reversed-generalized 2 Nearest-neighbor

For the consideration of the multiple copy-move forgery detection of digital images, and to avoid missing the matching feature points when generalized 2 Nearest-Neighbor (g2NN) algorithm is applied, Reversed generalized 2 Nearest-Neighbor (Rg2NN) algorithm is proposed. Reverse order is used in feature points matching, so that all feature points that match with the detected point can be calculated accurately. The experiment results show that the matching feature points calculated by Rg2NN are more accurate than by g2NN, and the ability of g2NN in detecting multiple copy-move forgery is improved. When one patch in the image is copied and pasted multiple times or two or more patches are copied and pasted, the copy-move map can be localized precisely by the Rg2NN algorithm.