Identification of splicing edges in tampered image based on Dichromatic Reflection Model
This addresses image forensics for detecting forgeries, but appears incremental as it builds on existing models with a specific application.
The paper tackles the problem of detecting splicing edges in tampered images by developing an optic-physical method based on the Dichromatic Reflection Model, which transforms images into S and o1o2 color space and uses composite gradients and photometric properties to classify edges, with experiments demonstrating its efficacy.
Imaging is a sophisticated process combining a plenty of photovoltaic conversions, which lead to some spectral signatures beyond visual perception in the final images. Any manipulation against an original image will destroy these signatures and inevitably leave some traces in the final forgery. Therefore we present a novel optic-physical method to discriminate splicing edges from natural edges in a tampered image. First, we transform the forensic image from RGB into color space of S and o1o2. Then on the assumption of Dichromatic Reflection Model, edges in the image are discovered by composite gradient and classified into different types based on their different photometric properties. Finally, splicing edges are reserved against natural ones by a simple logical algorithm. Experiment results show the efficacy of the proposed method.