MATLAB Code for Image Forgery Detection: Feature Extraction and Tampering Visualization

This MATLAB code implementation is designed for image forgery detection, incorporating multiple algorithmic approaches including robust feature extraction, detection of malicious alterations, and visualization of tampered regions. The code typically utilizes techniques such as frequency domain analysis through Discrete Cosine Transform (DCT) coefficients, noise inconsistency measurements, or copy-move detection algorithms that compare local image patches. Image forgery detection represents a critical challenge in the digital era, and this MATLAB solution provides essential tools for addressing this issue. By identifying manipulated images, this implementation helps protect digital image integrity and ensures reliable information transmission through automated tampering assessment. The code structure generally includes modules for pre-processing, feature extraction using methods like Local Binary Patterns (LBP) or Scale-Invariant Feature Transform (SIFT), classification algorithms for authenticity determination, and post-processing for result visualization with heat maps or boundary marking around detected forged areas.