Do Digital Images Tell the Truth?

Since the advent of digital cameras, editing tools have made content manipulation straightforward. Copy-move forgeries — where a region is duplicated and pasted within the same frame — are particularly hard for human observers to detect, yet they undermine the credibility of visual evidence.

This chapter surveys the state of the art in copy-move detection across feature representations, learning strategies and public datasets. We catalogue low-level descriptors, machine-learning pipelines and deep architectures, and discuss how each responds to common post-processing such as translation, rotation and scaling. We close on the open challenges in building explainable, trustworthy forensic systems.