PixelProof: Uncovering the Truth in Images

Authors- Professor Rinku Badgujar, Suryansh Khandelwal, Shriyog Borse, Nagesh Kannure, Manav Mayyank

Abstract-In the age of sophisticated digital manipulation, deepfake content poses significant threats to privacy, security, and information integrity. PixelProof addresses these challenges with an AI-powered system designed to detect deepfake and forged content in images and videos. Utilizing advanced machine learning and computer vision techniques, it analyzes inconsistencies such as pixel anomalies, lighting discrepancies, and facial distortions. PixelProof combines convolutional neural networks (CNNs) for spatial analysis and recurrent neural networks (RNNs) for evaluating temporal inconsistencies in videos. With real-time detection capabilities and detailed tampering reports, it empowers users to verify the authenticity of digital media. By promoting trust and combating misinformation, PixelProof ensures the reliability of visual content in a rapidly evolving digital world.

DOI: /10.61463/ijset.vol.12.issue6.340