Automatic Detection of Image Morphing by Topology-based Analysis

Topological Data Analysis (TDA) is an emerging framework for the understanding of Bigdata. This paper investigates and develops a TDA approach to image forensics that exploits the sensitivity to image tampering of a variety of persistent homological invariants of simplicial complexes constructed for certain automatically computed image texture landmarks. For each image, we construct sequences of simplicial complexes, whose vertices are the selected set of landmarks, for a sequence of distance thresholds and use a variety of homological invariants (e.g. number of connected components) to distinguish natural face images from morphed ones. We shall demonstrate the richness of TDA in dealing with image tampering by testing the performance of this approach on a large benchmark image dataset of passport photos in detecting various known morphing attacks.