Review on passive approaches for detecting image tampering

This paper defines the presently used methods and approaches in the domain of digital image forgery detection. A survey of a recent study is explored including an examination of the current techniques and passive approaches in detecting image tampering. This area of research is relatively new and only a few sources exist that directly relate to the detection of image forgeries. Passive, or blind, approaches for detecting image tampering are regarded as a new direction of research. In recent years, there has been significant work performed in this highly active area of research. Passive approaches do not depend on hidden data to detect image forgeries, but only utilize the statistics and/or content of the image in question to verify its genuineness. The specific types of forgery detection techniques are discussed below

A 3-D Stability Analysis of Lee Harvey Oswald in the Backyard Photo

Fifty years have passed since the assassination of U.S. President Kennedy. Despite the long passage of time, it is still argued that the famous backyard photo of Oswald, holding the same type of rifle used to assassinate the President, is a fake. These claims include, among others, that Oswald’s pose in the photo is physically implausible. We describe a detailed 3-D stability analysis to determine if this claim is warranted

Lighting and Optical Tools for Image Forensics

We present new forensic tools that are capable of detecting traces of tampering in digital images without the use of watermarks or specialized hardware. These tools operate under the assumption that images contain natural properties from a variety of sources, including the world, the lens, and the sensor. These properties may be disturbed by digital tampering and by measuring them we can expose the forgery. In this context, we present the following forensic tools: (1) illuminant direction, (2) specularity, (3) lighting environment, and (4) chromatic aberration. The common theme of these tools is that they exploit lighting or optical properties of images. Although each tool is not applicable to every image, they add to a growing set of image forensic tools that together will complicate the process of making a convincing forgery

Pixel and Edge Based Illuminant Color Estimation for Image Forgery Detection

AbstractImages are one of the powerful media for communication. Image security is a main issue in the fields that using digital images. By the development of high resolution cameras, personal computers and photo-editing software's, the manipulation of images is becoming common. This paper mainly focuses on common form of image manipulation such as image splicing. The process of analysis is done with the help of inconsistencies in illuminant color of images. Illumination inconsistencies detection is a powerful way for image forgery detection. Inconsistency detection among different images can be identified with the help of pixel and edge based illuminant color estimation on image regions. From these illuminant estimators, extract shape and color features, which is then provided to a classifier for making decision. Classification using SVM and its performance is evaluated using distinct testing process. The main contribution of this method is, how illuminant color estimation on various constraints can be exploited as a forgery detection method and how these are provided for decision-making with minimal user interaction

Recent Advances in Digital Image and Video Forensics, Anti-forensics and Counter Anti-forensics

Image and video forensics have recently gained increasing attention due to the proliferation of manipulated images and videos, especially on social media platforms, such as Twitter and Instagram, which spread disinformation and fake news. This survey explores image and video identification and forgery detection covering both manipulated digital media and generative media. However, media forgery detection techniques are susceptible to anti-forensics; on the other hand, such anti-forensics techniques can themselves be detected. We therefore further cover both anti-forensics and counter anti-forensics techniques in image and video. Finally, we conclude this survey by highlighting some open problems in this domain