Exposing Image Forgery through Contrast Enhancement

Today digital images may be used for several beneficial purposes such as evidence in court. Image forgeries may happen, so verification is needed to detect the authenticity of the image. Contrast enhancement is used for adjusting the brightness and contrast of a digital image. Malicious users may also perform contrast enhancement locally for creating a realistic composite image. Here proposes two algorithms, first for detecting the contrast enhancement based manipulation involved in JPEG compressed images and the second one is used for detecting composite image. First, we focus on the detection of global contrast enhancement applied to the previously JPEG-compressed images, which are widespread in real applications. The histogram peak/gap artifacts incurred by the JPEG compression and pixel value mappings are analyzed theoretically, and Receiver Operating Characteristic (ROC) curves are generated for evaluation. Second, we propose to identify the composite image created by enforcing contrast adjustment on either one or both source regions. The positions of detected blockwise peak/gap bins are clustered for recognizing the contrast enhancement mappings applied to different source regions.