State-of-the-Art Techniques for Image Forgery Detection: A Review

Abstract

Image forgery has become a widespread issue due
to the ease with which digital images can be manipulated and altered. As a result, the development of techniques for detecting image forgery has become an important area of research in the field of digital forensics. In this review, it provides an overview of various techniques for detecting image forgery, including both passive and active approaches. This paper discusses the pros and cons of each approach, as well as their performance in terms of detection accuracy, robustness, and other relevant metrics. It also
highlights the challenges and limitations of image forgery
detection, including the need for a comprehensive approach that combines multiple techniques and the potential for new and advanced tampering techniques. Our review concludes with a discussion of future directions and potential research areas in image forgery detection, including the use of emerging technologies such as machine learning and blockchain. Overall, our review provides a comprehensive overview of the current state of the art in image forgery detection and highlights the need for continued research and development in this important field.