Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India

Research Article

Effective Hand Gesture Recognition for Sign Language Communication using SVM and CNN Algorithms

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  • @INPROCEEDINGS{10.4108/eai.23-11-2023.2343251,
        author={Subha Indu S and Anuja  AV and Harshendra  M and Aishwarya  M and Bhagavath Kishore K and Rubanraj  J},
        title={Effective Hand Gesture Recognition for Sign Language Communication using SVM and CNN Algorithms},
        proceedings={Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India},
        publisher={EAI},
        proceedings_a={IACIDS},
        year={2024},
        month={3},
        keywords={support vector machines (svm) sign language image recognition machine learning},
        doi={10.4108/eai.23-11-2023.2343251}
    }
    
  • Subha Indu S
    Anuja AV
    Harshendra M
    Aishwarya M
    Bhagavath Kishore K
    Rubanraj J
    Year: 2024
    Effective Hand Gesture Recognition for Sign Language Communication using SVM and CNN Algorithms
    IACIDS
    EAI
    DOI: 10.4108/eai.23-11-2023.2343251
Subha Indu S1,*, Anuja AV1, Harshendra M2, Aishwarya M2, Bhagavath Kishore K2, Rubanraj J2
  • 1: Assistant Professor, Department of Software Systems, Sri Krishna Arts and Science College
  • 2: Students, Department of Software Systems, Sri Krishna Arts and Science College
*Contact email: subhaindus@skasc.ac.in

Abstract

The recognition system follows the principle of dynamic sign language. Deaf (hard of hearing) mostly utilize sign language to communicate inside and with other members of their community. With the help of this technology, the users will have the ability to learn and understand sign language. At present sign language system mostly depends on pricey external sensors. To extract useful data, collecting datasets and various extraction techniques are been used. This extracted data is used as input for various learning techniques. This proposal proposes to give people with disabilities a learning tool to help them recognize and understand Sign Language Symbolization. Although existing systems can recognize sign language with sufficient accuracy, this proposal also uses live video feed recognition. It offers more interactivity as a result than current systems do.