Paper Key : IRJ************966
Author: Shreya G Attimarad,Sanjana A N,Shraddha M K,Shwetha K
Date Published: 07 Jan 2023
Abstract
A disability that hinders a person's capacity for verbal communication is linguistic impediment. Among the most structured languages is sign language, which would be designed to address this issue. There seems to be undeniably a requirement for a system or software program which can detect sign language gestures, allowing for communication even with individuals who do not understand sign language. A real-time system was developed with the aid of machine learning and image processing. Pre-processing images and eradicating multiple hands from the background are both done via image processing. These images, which were taken after the background was removed, were used to create data that contained the 26 English alphabets. Indeed a customized dataset and spontaneous hand gestures performed by individuals of varied complexion have been employed to evaluate the convolutional neural network that has been proposed here.
DOI LINK : 10.56726/IRJMETS32712 https://www.doi.org/10.56726/IRJMETS32712