• PRANJAL SANJAY JAGTAP
• Mr.AKASH MHETRE
• ANKITA SANJAY MAHADIK
• PRAJAKTA SUKHDEO KARANDE
• AISHWARYA RAVINDRASINGH RAJPUT

This project introduces a web-based application for Sign Language Detection aimed at reducing the communication barriers between the hearing-impaired and the broader community. Leveraging a real-time webcam feed, the system captures hand gestures and translates them into readable text using machine learning algorithms. Developed using the Django web framework, the application incorporates a pre-trained sign language recognition model to ensure accurate detection of gestures. It features an intuitive user interface, including functionalities such as user authentication and real-time camera-based gesture recognition. The system architecture includes components for data acquisition, landmark detection, and model training, allowing for continuous updates and improvements. Ultimately, the project strives to enhance accessibility and foster inclusivity by providing an intelligent tool for recognizing sign language.

Sign Language Detection, Image Processing, Gesture Recognition, Communication Accessibility.

"Sign Language Detection and Translation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.a692-a698, May-2025, Available :http://www.jetir.org/papers/JETIR2505074.pdf

"Sign Language Detection and Translation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppa692-a698, May-2025, Available at : http://www.jetir.org/papers/JETIR2505074.pdf