A Comparative Study of Copy-Move Forgery Detection Methods in Digital Images
Published: 2025
Author(s) Name: Muthireddy Rajesh, Bokka Sitaram Reddy and Votte Rajashekhar |
Author(s) Affiliation: Computer Science and Engg., Malla Reddy Engineering College for Women, Hyderabad, Telangana, India.
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Abstract
One of the most popular and dishonest image tampering methods is Copy-Move Forgery (CMF), in which a portion of an image is copied and pasted inside another image to hide or change information. It is a common technique for digital manipulation because of its simplicity, which is made possible by widely accessible editing tools. It can be difficult to identify these forgeries, though, particularly if the copied areas undergo post-processing techniques like noise addition, rotation, or scaling. Many algorithms have been created over time to locate and identify CMF; most of them use a similar pipeline, but they vary in how they extract features and match them. Four detection techniques are compared in this paper using images that contain randomly shaped copied regions. The assessment focusses on their efficacy and efficiency, as determined by F-Score, execution time, precision, and recall, offering insights into the advantages and disadvantages of each strategy.
Keywords: Copy-move, DCT, DWT, Feature matching, Image forgery.
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