Special Issue Article Open Access

Tampering and Copy-Move Forgery Detection Using Sift Feature

Abstract

As society has become increasingly depend upon digital images to communicate visual information. Image would provide better impact in convincing someone of something rather than pure description by word. Nowadays one of the principal means for communication is digital visual media. Digital image widely used in various field like medical imaging, journalism, scientific manipulation and digital forensics. Digital image forgery creates more problems on real world. In most digital image communication the main problem is its authenticity. Digital image forensics is a brand new research field which aims at finding the authenticity of images by recovering information. There are several different tampering attacks but, surely, one of the most common and immediate one is copy-move. COPY-MOVE forged detection identified by the visual local feature of images. SIFT method are find the local feature and cluster the related close points, and Geometric transformation are used to identified the similarity and dissimilarity of the images. Then identified the Tampering on images. This Tampering detection is used to identify image Authentic or not.

N.Anantharaj

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