Passive Digital Image Forgery Detection Techniques and Implementation

Abstract: In today’s world image authenticity is very important in many social areas. With the advent of low-cost and high-resolution digital cameras, and sophisticated photo editing software, such as Adobe Photoshop, GIMP, etc. digital images can be easily manipulated and tampered. When creating a digital forgery, it is often necessary to combine several images, for example, when compositing one person’s head onto another person’s body. If these images were originally of different JPEG compression quality, then the digital composite may contain a trace of the original compression qualities. We detect this type of tampering using JPEG ghost detection technique. We describe how resampling (e.g., scaling or rotating) introduces specific statistical correlations, and describe how these correlations can be automatically detected in any portion of an image using EM algorithm. Most digital cameras, for example, employ a single sensor in conjunction with a color filter array (CFA), and then interpolate the missing color samples to obtain a three channel color image. This interpolation introduces specific correlations which are likely to be destroyed when tampering with an image. We quantify the specific correlations introduced by CFA interpolation, and describe how these correlations, or lack thereof, can be automatically detected in any portion of an image. In this way, this paper describes some of the passive digital image forgeries like JPEG Ghost, resampling and CFA interpolation.

Keywords: Authenticity, Forgery, Types of forgery, Passive forgery detection, JPEG ghost, EM algorithm, CFA interpolation.