Topological Data Analysis for Image Forgery Detection (Indian Journal of Forensic Medicine & Toxicology, 2020)
The manipulation of digital images has become easy due to powerful computers, advanced photo-editingsoftware packages and high-resolution image-capturing devices. The identification of image authenticityhas received much attention because of the increasing power of image editing methods. Object removal isan image forgery technique, which is usually achieved by the Exemplar-Based Inpainting (EBI) methodwithout any noticeable traces. Some legal issues may arise when a tampered image cannot be distinguishedfrom a real one by visual examination. Therefore the manipulation of digital images has become a hugechallenge to passive image forensics. There are a lot of forgery techniques that use to detect on these imagesafter removing the object, but these techniques have limitations when used some post-processing operationssuch as super-resolution processing, noise addition, blurring and compression processes. To address thisissue, this paper proposes a novel forgery detection technique to recognize tampered inpainting images,using topological data analysis (TDA) approach. TDA is a mathematical approach concern studying shapesor objects to gain information about connectivity and closeness property of those objects. This proposedtechnique is applied for a large number of natural images with getting a good results.