Detection of CopyMove Forgery in Digital Image Based on SIFT Features and Automatic Matching Thresholds. Today the technology age is characterized by the spread of the digital images. Itxe2x80x99s the most common form of information transmission whether through the internet or newspaper. This huge use of images technology has been accompanied by an evolution in editing tools which makes modifying and editing an image very simple. This paper proposes an effective and fast method for copymove forgery detection. The paper adopts a SIFT technique for features extraction and wavelet technique to estimate the matching threshold. The lowfrequency components are used to compute a dynamic threshold rather than a fixed threshold. Also, a method to remove false positive areas is proposed in order to produce the best possible results. The method can detect accurately and quickly the forgery even after more complex transformations. The experimental results refer that the proposed method can also detect forgery against postprocessing operation and multiple copies.

Copy and Move Forgery Detection Using SIFT and Local Color Dissimilarity Maps It is becoming harder and harder to believe in digital images authenticity. This is due to the increasing ease of producing forged images using retouching software more powerful than ever. On software like Photoshop, one can easily remove an element from an image with just a few clicks. Copymove is one of the elemental forgery methods that consists in the duplication of one portion of the image. Such manipulation is very usual and dangerous in official document falsification (ID, breeder docs, bills. . . ). In this paper, we propose a novel method for the detection of Copy and Move forgery while maintaining a low false positive rate.