Image Forgery Detection –Survey on Key Areas of Research Approaches and Challenges

In the era of digital media and social networking, the proliferation of manipulated images has become a significant concern, leading to the spread of misinformation and fake news. Detecting these forged images is crucial for maintaining the integrity of digital content and ensuring trustworthiness in online communication. This review paper provides a comprehensive overview of image forgery detection techniques, covering traditional methods as well as recent advancements in deep learning approaches. The review begins by outlining the different types of image forgeries, including copy-move, splicing, and manipulation, and their implications in various contexts. Subsequently, this paper discusses on Traditional techniques for forgery detection, such as image processing algorithms and feature-based methods, are discussed, along with their limitations and challenges.