Differentiating synthetic and optical zooming for passive video forgery detection: An anti-forensic perspective

A video can be manipulated using synthetic zooming without using the state-of-the-art video forgeries. Synthetic zooming is performed by upscaling individual frames of a video with varying scale factors followed by cropping them to the original frame size. These manipulated frames resemble genuine natural (optical) camera zoomed frames and hence may be misclassified as a pristine video by video forgery detection algorithms. Even if such a video is classified as forged, forensic investigators may ignore the results, believing it as part of an optical camera zooming activity. Hence, this can be used as an anti-forensic method which eliminates digital evidence. In this paper, we propose a method for differentiating optical camera zooming from synthetic zooming for video tampering detection. The features used for this method are pixel variance correlation and sensor pattern noise. Experimental results on a dataset containing 3200 videos show the effectiveness of the proposed method.