Object based Image Splicing Localization using Block Artificial Grids

Abstract

People share pictures freely with their loved ones and others using smartphones or social networking sites. The news industry and the court of law use the pictures as evidence for their investigation. Simultaneously, user-friendly photo editing tools alter the content of pictures and make their validity questionable. Over two decades, research work is going on in image forensics to determine the picture's trustworthiness. This paper proposes an efficient statistical method based on Block Artificial Grids in double compressed images to identify regions attacked by image manipulation. In contrast to existing approaches, the proposed approach extracts the artefacts on individual objects instead of the entire image. A localized algorithm is proposed based on the cosine dissimilarity between objects and exploit the tampered object with maximum dissimilarity among objects. The experimental results reveals that the proposed method is superior over other current methods.