Image Forgery Detection

Abstract

Over the past five years, the field of digital forensics has emerged to help restore some trust to digital images. Here I review the state of the art in this new and exciting field. In contrast to these approaches, passive techniques for image forensics operate in the absence of any watermark or signature. These techniques work on the assumption that although digital forgeries may leave no visual clues that indicate tampering, they may alter the underlying statistics of an image. The set of image forensic tools can be roughly grouped into five categories: Pixel-based techniques that detect statistical anomalies introduced at the pixel level; format-based techniques that leverage the statistical correlations introduced by a specific lossy compression scheme; camera-based techniques that exploit artifacts introduced by the camera lens, sensor, or on-chip post processing; physically based techniques that explicitly model and detect anomalies in the three-dimensional interaction between physical objects, light, and the camera; and geometric-based techniques that make measurements of objects in the world and their positions relative to the camera.

Existing System

The drawback of this approach is that a watermark must be inserted at the time of recording, which would limit this approach to specially equipped digital cameras. In contrast to these approaches, passive techniques for image forensics operate in the absence of any watermark or signature. Digital image forgeries can be detected using Chromatic Aberration, by exploiting Sensor Pattern Noise. Digital image forgeries can be exposed by analyzing Color Filter Array Interpolation. A variety of principles of Optical Physics like lighting inconsistencies are applied to establish the state of an image. Most recently, Fourier Mellin Transform (FMT) and 1-D projection of log-polar values were applied to make the image forgery detection a more robust scheme.

Proposed System

Our Approach Technology allows digital media to be altered and manipulated in ways that were simply impossible 20 years ago. Tomorrow’s technology will almost certainly allow us to manipulate digital media in ways that today seem unimaginable. And as this technology continues to evolve, it will become increasingly important for the science of digital forensics to try to keep pace. There is little doubt that as we continue to develop techniques for exposing photographic frauds, new techniques will be developed to make better fakes that are harder to detect. While some of the forensic tools may be easier to fool than others, some tools will be difficult for the average user to circumvent. For example, once disturbed, the color filter array interpolation can be regenerated by simply placing an image onto its original lattice and reinterpolating each color channel. On the other hand, correcting for inconsistent lighting is nontrivial in a standard photo-editing software program.

Architecture