Hand Gesture translation using AI

This project was inspired by the need to bridge the communication gap between deaf–mute individuals and the hearing community. We built a system that captures hand gestures through a camera, processes them, and uses a CNN model to recognize and translate signs into text. During development, we faced challenges such as limited datasets, varying backgrounds, and accurate hand segmentation. Despite this, we successfully created a high-accuracy, hardware-free recognition system using deep learning. Through this work, we learned how to preprocess images effectively, design and train CNN models, and improve gesture recognition using augmentation and tuning.