Visual Math Interpreter using OpenCV and Generative AI

This research presents a web-based Visual Math Interpreter designed to enhance human-computer interaction for mathematical problem solving using OpenCV and Generative AI. The system supports two intuitive input methods: real-time hand gesture-based drawing of mathematical expressions and image uploads containing handwritten or printed equations. Hand gestures are captured and processed using machine vision techniques, enabling users to draw directly on a virtual canvas. Uploaded or hand-drawn equations are interpreted and solved using a multimodal generative AI model, which provides both the solution and a concise explanation. By integrating OpenCV, MediaPipe, and Generative AI, the platform delivers real-time feedback through an interactive and user-friendly interface. The proposed system demonstrates an efficient and engaging approach to mathematical interaction, particularly suited for educational environments and touch-free computing scenarios.