Detecting spliced face in a group photo using PCA

Abstract

Digital image tampering detection has become an active research area in the recent decade. Among the different types of image tampering, manipulation involving facial regions are of great interest as innocents are often victimized for unlawful benefits. Image splicing is a kind of image tampering where an image region is copied from one image and pasted onto another image. Principal component analysis is applied on facial regions extracted from illuminant maps to identify the facial region copy-pasted onto a group photo. Experiments were conducted on statistics-based and physics-based illumination maps and results showed that the method achieved a true positive rate of 62% and 64% respectively.