Exposing structural tampering in digital images

Manipulation in a digital image may appear because of unintentional or harmless post-processing of the image, such as through JPEG compression or contrast enhancement. But some manipulations or tampering in a digital image are done with malicious motivation. One may find standard techniques to identify and analyze many types of such manipulations. But with the phenomenal growth in processing power of image capturing devices and user-friendly complex post-processing software, it has become a real challenge to find a technique that could tell exactly where, on the image, the tampering has been done. We propose a new method that could identify the block where structural tampering has been done. This method automatically ignores the impact of harmless changes in the digital image. Our proposal is based on the unique feature of each image that is described by the hash function. We find the correlation coefficients of the original image and the tampered image with respect to a reference image and establish that the difference of these two correlation coefficients is significantly larger, hence exposing the tampering. The method is tested on a database of images conforming to our theoretical analysis.