Copy Move Image Forgery Detection Using CNN

Abstract

Digital images are crucial in various fields, and image forgery, a practice where individuals alter images to conceal or present false information, is becoming more prevalent with advanced image processing tools. The proposed system aims to identify and expose copy-move forgery, a common manipulation technique in which a portion of an image is copied and pasted within another picture, copy-move forgery is what the suggested system seeks to detect and reveal. Singular Value and Discrete Cosine Transform (DCT)-based methods are also reliable. Decomposition (SVD) was established in order to improve resilience against standard post-processing procedures. Additionally, better algorithms using Local Binary Histograms of the pattern (LBP) show superior ability to locate and identify copy-move frauds amongst different datasets. These developments demonstrate the continual initiatives to raise the precision and effectiveness of techniques for detecting image fraud.