Image Tampering Blind Detection Using Fourier Transform

This document discusses blind detection of image tampering using Fourier transform and implements this process with MATLAB. The Fourier transform serves as a powerful mathematical tool that converts signals or images from the temporal/spatial domain to the frequency domain. By applying Fourier transform analysis, we can examine spectral information within images to identify potential tampering artifacts. In MATLAB implementation, key functions like fft2() for 2D Fast Fourier Transform and fftshift() for frequency domain visualization are utilized to process image data. The algorithm typically involves converting the input image to grayscale, applying Fourier transform, analyzing frequency spectrum patterns for anomalies, and employing threshold-based detection mechanisms. This blind detection system helps identify potential image manipulations without requiring reference images, thereby enhancing image integrity and reliability through automated frequency-domain analysis. The MATLAB code structure would include image preprocessing, Fourier transformation, spectral analysis modules, and tampering indication outputs.