Copy-Move Image Tampering Detection Algorithm Implementation

This project presents a MATLAB-based implementation of the copy-move image tampering detection algorithm, designed to identify duplicated regions within digital images. The algorithm employs sophisticated block-based analysis techniques where the input image is divided into overlapping blocks, typically using functions like `im2col` for efficient block processing. Each block undergoes feature extraction using methods such as Discrete Cosine Transform (DCT) coefficients or Speeded-Up Robust Features (SURF), implemented through MATLAB's image processing toolbox functions. The core detection mechanism involves lexicographical sorting of feature vectors using `sortrows` function and calculating similarity metrics between adjacent blocks to identify potential copied regions. The algorithm incorporates threshold-based decision making with functions like `pdist2` for distance calculation and morphological operations using `imerode`/`imdilate` for post-processing detected regions. This implementation demonstrates high efficiency in processing various image types including digital photographs and scanned images, providing reliable tampering detection while maintaining computational performance through optimized matrix operations inherent to MATLAB's environment. Users can leverage this algorithm to effectively detect and prevent image forgery, thereby preserving image authenticity and integrity in digital forensics applications.