Sign Language Detection system

About This Project

A Sign Language Detection system using Machine Learning to recognize hand gestures and translate them into meaningful text.

The Sign Language Detection project is an AI/ML-based application designed to recognize and interpret hand gestures used in sign language. The system uses image input captured through a camera and processes it using computer vision techniques.

The input data is preprocessed using OpenCV for hand detection, image normalization, and feature extraction. A Convolutional Neural Network (CNN) model is trained on a labeled dataset of sign language gestures to classify different signs accurately. The trained model is evaluated using performance metrics such as accuracy and loss.

The detected gestures are mapped to corresponding characters and displayed as text output, enabling communication support for hearing-impaired users. This project demonstrates practical implementation of deep learning, supervised learning, and real-time gesture recognition, making it a strong major AI/ML project.