A classifier design for detecting image manipulations

Abstract

In this paper we present a framework for digital image forensics. Based on the assumptions that some processing operations must be done on the image before it is doctored, and an expected measurable distortion after processing an image we design classifiers that discriminates between original and processed images. We propose a novel way of measuring the distortion between two images one being the original and the other processed. The measurements are used as features in classifier design. Using these classifiers we lest whether a suspicious part Of a given image has been processed with a particular method or not. Expermental results show that with a high accuracy we are able to tell if some part of an image has undergone a particular or a combination of processing methods.