Exposing Digital Forgeries by Detecting Duplicated Image Regions

Abstract

We describe an efficient technique that automatically detects duplicated regions in a digital image. This technique works by first applying a principal component analysis to small fixedsize image blocks to yield a reduced dimension representation. This representation is robust to minor variations in the image due to additive noise or lossy compression. Duplicated regions are then detected by lexicographically sorting all of the image blocks. We show the efficacy of this technique on credible forgeries, and quantify its robustness and sensitivity to additive noise and lossy JPEG compression.