AI-Enhanced Photo Authenticity: A User-Focused Approach to Detecting and Analyzing Manipulated Images

In the digital age, the authenticity of photographs is increasingly questioned due to the rise of sophisticated AI and human manipulation techniques. This paper presents the development of an AI-assisted system designed to aid users in identifying and verifying the genuineness of photos. Unlike fully automated solutions, our approach emphasizes user empowerment, providing tools to enhance human expertise in photo authentication. The system integrates advanced algorithms to detect potential manipulations and localize regions of interest, directing users’ attention to specific areas that warrant closer examination. Users can conduct more efficient and effective authenticity checks without scrutinizing the entire image by focusing on these targeted regions. Our goal is to augment, not replace, the critical role of human judgment in verifying photo authenticity. The system’s design and implementation are discussed, along with case studies demonstrating its practical application in various scenarios. This research aims to contribute to the growing field of digital forensics by providing a robust, user-friendly tool that bridges the gap between AI capabilities and human expertise in photo verification.