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Robust Copy-Paste Detection Algorithm using SIFT for Digital Image Forensics
Author(s) -
. Monika,
Dipali Bansal
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d7841.118419
Subject(s) - scale invariant feature transform , computer science , artificial intelligence , computer vision , image (mathematics) , digital image , software , pattern recognition (psychology) , image processing , programming language
Forensics of images verifies the authenticity of digital images. Because of the easier availability of software, manipulation of images has become quicker and easier. Image composition, copy-paste, multiple cloning, splicing, etc have become a common practice. The paper proposes a robust algorithm for the detection of duplicity using Scale Invariant Feature Transform (SIFT) approach. Copied location of an image is occasionally pasted in another place of the identical image or in another image, which creates difficulties in detecting the copy-paste region and identifying the located region as well as creates inefficiency in the accuracy of forgeries. We developed an approach that shows improved techniques through runtime optimizations and compared various parameters with existing methodologies in order to obtain highly correlated image areas for detecting the manipulated regions. The proposed approach can detect copy-paste forgeries effectively with high accuracy, reliability, and inconsistencies regardless of the test scenario.

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