An Overview of Passive Digital Image Tampering Detection Methods

Forgery detection and digital image authentication are important tasks in digital image forensics. Various methods for forgery detection and digital image authentication have been proposed and evaluated in the literature, typically based on neural networks and deep learning, image processing algorithms, mathematical techniques, and image blocks and keypoints detection. Passive image forgery detection methods, unlike active methods, do not require any previously embedded information to establish the authenticity of an image. This paper provides an overview of passive digital image tampering detection methods and highlights strengths, limitations, and potential areas for improvement of each proposed approach, with particular emphasis on techniques used to identify copy-move forgeries.