LAUSR

Forgery involving region duplication is one of the most common types of video tampering. However, few algorithms have been suggested for detecting this type of forgery effectively, especially for videos to which a mirroring operation was applied. In this paper, we summarize the properties of duplication forgery of video regions and propose a novel algorithm to detect this forgery. First, the algorithm extracts the feature points in the current frame. The tampered areas in the current frame are then searched, which is implemented in three steps. Finally, our algorithm detects the tampered areas in the remaining frames using spatio-temporal context learning and outputs the detection results. The experimental results demonstrate the satisfactory performance of our algorithm for detecting videos subjected to mirror operations and its higher efficiency than previous algorithms.