A Novelty Approach on Forgery Digital Image Detection based Image Source Identification ANN

In imaging science, the photo editing software packages can alter the original images without any detecting traces of tampering. Hence, the image forgery detection technique plays an important role in verifying the integrity of digital image forensics for authentication. The techniques such as watermarking are used for authentication but it can be modified through third parties attack through extraction. Malicious and digital imaging (digital products) tamper detection is the subject of this article. In particular, we focus on a special type of digital forgery detection copy attack campaign, in which part of the image is copied and pasted into the image and the cover features a large image of intentions another. In this paper, we investigate the dynamic forged copy detection problem, and describes a highly efficient and reliable detection method that based on image source ANN identification.. Even when the region is enhanced copy / retouching and background merger, and the method can successfully identify counterfeit forgery when images are saved in a lossy format (such as JPEG). The performance of the method's performance several forged images.