Detection of interpolation using correlation coefficients
Hongjian Cao, Yao Zhao, Rongrong Ni · 2012
Resampling detection is a very useful tool in digital image forensic. In this paper, we propose a new algorithm for detecting interpolation by using the periodicity characteristics hidden among the rows(or columns) of the image. The core of our algorithm is the use of correlation coefficients based on the observation that the correlation coefficients of the row(or column) vectors vary periodically in resampled image. In some images, the image contents themselves correlate periodically. To reduce this kind of interference and enhance the detection efficiency, we use the first derivatives signals and detect the image both horizontally and vertically under some condition. As experiments show, the proposed algorithm works well, and most of the resampling factors can be correctly determined with high accuracy.