Hand Gesture Recognition using Machine Learning

Registration ID: IJNRD_223578

Published ID: IJNRD2406248

DOI: Click Here to Get

Nidhi Ternikar , Palash kalghatgi , Mrutyunjaya Emmi

Sign language is a visual language that uses hand motions, changes in hand shape, and track information to convey meaning. It is the primary mode of communication for those with hearing and language impairments. The use of sign language for communication is limited, despite the fact that sign language recognition can help a large number of such persons deal with regular people. As a result, there is a need to create a more comfortable approach for people with hearing and language impairments to learn and work in order to improve their lives. Therefore, the basic idea behind this article is to make the communication between normal human beings and deaf people much easier. In order to recognize static gestures associated with sign language alphabet and a few commonly used words, we conducted a comprehensive research study employing the hand tracking technique Mediapipe and a gesture classification model based on Support Vector Machine (SVM). The results of the experiments are validated using Recall, F1 Score and Precision. Based on the validated results, we recommend the application of the discussed techniques for such communication. The suggested methods have high generalization qualities and deliver a classification accuracy of around 99 percent on 26 alphabet letters, numerical digits, and some regularly used words[4].

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Nidhi Ternikar, Palash kalghatgi, & Mrutyunjaya Emmi (June-2024). Hand Gesture Recognition using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(6), c481-c486. https://ijnrd.org/papers/IJNRD2406248.pdf

Volume 9 Issue 6, June-2024

Pages : c481-c486

Paper Reg. ID: IJNRD_223578

Published Paper Id: IJNRD2406248

Downloads: 000121986

Research Area: Master of Computer Application 

Country: Belagavi , Karanataka , India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2406248.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2406248

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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