Digital Image Forgery Detection using Convolutional Neural Network (CNN): A Survey

Nowadays, there are lots of pictures everywhere because almost everyone has a camera or a smartphone. This has led to a worrying trend: people change images for different reasons. While digital images are powerful tools for information exchange, they are also susceptible to exploitation for political, cultural, economic, and social purposes through the dissemination of falsified information. The widespread availability of sophisticated image editing software has significantly lowered the barriers to image manipulation, making it challenging to detect such forgeries. These manipulated images can have far-reaching consequences, affecting fields such as medical diagnosis, legal judgments, politics, and insurance claims. This paper delves into the realm of forgery detection, a vital domain within machine vision. It comprehensively examines the techniques employed to manipulate digital images and offers a detailed review of existing methodologies for digital image forgery detection.