This paper presents passive blind forensic scheme to detect spatial tampering in MPEG-4 (Moving Picture Experts Group-4) digital video. In spatial tampering, small region of frame is copied and pasted at some other location in same frame. A proposed algorithm uses SIFT (Scale Invariant Feature Transform) and RANSAC (Random Sample Consensus) to detect the tampering. In this local features from each frame are extracted using SIFT and those features are matched to identify forged area. At the end RANSAC homography is used to remove the false matching to increase the detection accuracy. The proposed method performance is measured with respect to detection accuracy and computational time and verified on compressed and uncompressed videos. To create test data various geometric alterations used in forgery such as scaling, rotation are considered. The simulation results proves that the proposed method finds the forged area efficiently for all the above mentioned cases with average detection accuracy of 99.5%. The algorithm is tested for various compression rates to check its robustness. The detection accuracy of the algorithm increases as the compression rate increases. The performance of the proposed algorithm is compared with two other methods reported in literature which shows that the proposed scheme has higher detection accuracy compared to other methods. The average computational time observed is 0.56 seconds.

Spatial tampering, Forgery detection, SIFT, RANSAC, Forensic scheme

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