International Journal of Science, Engineering and TechnologyAuthors: Assistant Professor MR.G.K.Harinadh, Aneesa Shaik, Nuthi Vyshnavi,, Kurra Srivalli,, Madiraju Bhargavi
Abstract: Sign language is an essential way for people with hearing and speech impairments to communicate. However, for those who don’t know it, understanding sign language can be difficult.This paper introduces a real-time Indian Sign Language (ISL) recognition and translation system that uses deep learning and computer vision techniques. The application captures video from a webcam, identifies ISL gestures, and translates them into a spoken language like English, allowing for easy interaction.To accurately interpret hand movements, the system uses a Convolutional Neural Network (CNN) model trained on a tailored ISL dataset. A thorough preprocessing pipeline, which includes background removal, contour detection, and image normalization, improves the model’s performance under varying lighting and environmental conditions.
