Detection of Human Composite Images Based on EM Algorithm

A digitally altered image,often leaving no visual clues of having been tampered with,can be indistinguishable from an authentic image.The tampering,however,may disturb some underlying statistical properties of the image.Considering the scenario in which a digital forgery is created by splicing together two or more human images.In order to create a convincing match,it is often necessary to re-size,rotate,or stretch the images,or portions of them.This procedure typically requires re-sampling an image onto a new sampling lattice using an interpolation technique.Although a re-sampled image is often imperceptible,it contains specific correlations that,when detected,may represent evidence of tampering.The EM algorithm is recently used for the re-sampling detection.The thesis studies the detection of the re-sampling in image tampering.