Abstract
This paper introduces a novel area of research to the Image Forensic field; identifying High Dynamic Range (HDR) digital images. We create a test set of images that are a combination of HDR and standard images of similar scenes. We also propose a scheme to isolate fingerprints of the HDR-induced haloing artifact at “strong” edge positions, and present experimental results in extracting suitable features for a successful SVM-driven classification of edges from HDR and standard images. A majority vote of this output is then utilised to complete a highly accurate classification system.