Copy- Move Attack Forgery Detection by using SIFT
Swapnil H. Kudke1, A. D. Gawande2
1Mr. Swapnil H. Kudke, Department of Electronics and Telecommunication, Sipna College of Engineering and Technology, Amravati (Maharashtra), India.
2Dr. Avinash D. Gawande, Head, Department of Computer Science, Sipna College of Engineering and Technology, Amravati (Maharashtra), India.
Manuscript received on 15 April 2013 | Revised Manuscript received on 22 April 2013 | Manuscript Published on 30 April 2013 | PP: 221-224 | Volume-2 Issue-5, April 2013 | Retrieval Number: E0752042413/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Due to rapid advances and availabilities of powerful image processing software’s, it is easy to manipulate and modify digital images. So it is very difficult for a viewer to judge the authenticity of a given image. Nowadays, it is possible to add or remove important features from an image without leaving any obvious traces of tampering. As digital cameras and video cameras replace their analog counterparts, the need for authenticating digital images, validating their content and detecting forgeries will only increase. For digital photographs to be used as evidence in law issues or to be circulated in mass media, it is necessary to check the authenticity of the image. So In this paper, describes an Image forgery detection method based on SIFT. In particular, we focus on detection of a special type of digital forgery – the copy-move attack, in a copy-move image forgery method; a part of an image is copied and then pasted on a different location within the same image. In this approach an improved algorithm based on scale invariant features transform (SIFT) is used to detect such cloning forgery, In this technique Transform is applied to the input image to yield a reduced dimensional representation, After that Apply key point detection and feature descriptor along with a matching over all the key points. Such a method allows us to both understand if a copy–move attack has occurred and, also furthermore gives output by applying clustering over matched points.
Keywords: Tampering, Image Forgery, Copy-Move Attack, Scale Invariant Features Transform (SIFT), Cloning Forgery.
Scope of the Article: Image Security