Abstract: Communicating with the person who is having hearing disability is always a major challenge. The work presented in the paper is an exertion (extension) towards examining the difficulties in classification of characters in Indian Sign Language (ISL). Sign language is not enough for communication of people with hearing ability or people with speech disability. The gestures made by the people with disabilities get mixed or disordered for someone who has never learnt this language. Communication should be in both ways. In this paper, we introduce Sign Language recognition using Indian Sign Language. The user must be able to capture images of hand gestures using a web camera in this analysis, and the system must predict and show the name of the captured image. The captured image undergoes a series of processing steps which include various Computer vision techniques such as the conversion to gray-scale, dilation and mask operation. To train our model and identify the pictures we can use Convolutional Neural Network (CNN). Our model has achieved accuracy about 95%.

Keywords: Indian Sign Language (ISL), hearing disability, Convolutional Neural Network (CNN), Communication.

PDF | DOI: 10.17148/IJARCCE.2022.114189

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