Advanced Image Forensics: Detecting and reconstructing Manipulated Images with Deep Learning.
Keywords:
Image Forensics, Deep Learning, Manipulation Detection, Image Reconstuction, CNN, Authenticity Classification, Error Level Analysis, Wavelet Denoising,GANs.Abstract
This project presents a comprehensive approach to image forensics, combining deep learning techniques for manipulation detection and image reconstruction. Using Convolutional Neural Networks (CNNs), we accurately classify images as authentic or manipulated, leveraging preprocessing methods like Error Level Analysis (ELA) and wavelet denoising. Additionally, we explore Generative Adversarial Networks (GANs) for image reconstruction, enabling the identification of manipulated regions and assessing alterations' extent. Through experimental evaluation, our approach demonstrates robustness in detecting and analyzing manipulated images, offering a versatile solution for digital forensics and media authentication.
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