Sign Recognition for Disabled People

Abstract

Sign recognition for disabled people is an innovative assistive technology developed to reduce communication barriers between hearing- and speech-impaired individuals and the wider community. Communication is essential in daily life, yet many people with disabilities experience difficulties because sign language is not commonly understood. This research proposes an intelligent real-time gesture recognition system that interprets hand signs and converts them into readable text and audible speech.The proposed model uses computer vision, image processing, and machine learning techniques to identify hand gestures captured through a camera. Input images are preprocessed using noise removal, background separation, and contrast enhancement methods to improve recognition accuracy. Relevant gesture features such as hand contour, orientation, finger positions, and movement patterns are extracted and supplied to a trained classification model for sign identification.Once a gesture is recognized, the system instantly translates it into text and speech output, allowing smooth interaction between disabled users and non-sign-language users. The system is designed to be affordable, portable, and user-friendly, making it suitable for educational institutions, hospitals, offices, and public spaces. Experimental results indicate that the proposed approach achieves reliable recognition accuracy under normal lighting conditions.This work contributes to inclusive communication by empowering disabled individuals with greater independence and social participation. Future improvements may include multilingual speech generation, larger vocabulary support, and mobile deployment for wider accessibility.

DOI: https://doi-ds.org/doilink/04.2026-31295868