Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)

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Performance Analysis of CNN-Based Indian Sign Language Recognition

Authors
Nitin Sharma1, Jyotishka Mandal1, Aryan Chaudhury1, V. Sumitra1, *
1SRM Institute of Science and Technology, Kattankulathur, Tamilnadu, India
*Corresponding author. Email: sumitrav@srmist.edu.in
Corresponding Author
V. Sumitra
Available Online 30 June 2025.
DOI
10.2991/978-94-6463-754-0_3How to use a DOI?
Keywords
Indian Sign Language (ISL); gesture recognition; embedded systems; machine vision; convolutional neural networks (CNN); OpenCV; TensorFlow; Keras; real-time recognition; hand detection; image preprocessing
Abstract

Sign languages are a form of non-verbal communication where bodily movements convey specific messages. Sign language involves gestures that have distinct meanings within a cultural or social context. These gestures, however, can vary significantly across different societies. In recent years, the field of computer vision has seen growing interest in recognizing sign language to enhance communication between hearing and speech-impaired individuals and the broader population. Indian Sign Language (ISL) [1], which serves as a vital communication tool for millions in India, remains unfamiliar, thus creating a communication barrier. The research addresses the lack of robust systems for Indian Sign Language (ISL) recognition due to its unique challenges, including the use of both hands for most gestures, regional variations, and the absence of diverse datasets. This project seeks to overcome this challenge by designing an affordable system that recognizes ISL [2] gestures and translates them into speech or text, thereby providing greater accessibility and inclusivity.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
Series
Atlantis Highlights in Engineering
Publication Date
30 June 2025
ISBN
978-94-6463-754-0
ISSN
2589-4943
DOI
10.2991/978-94-6463-754-0_3How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Nitin Sharma
AU  - Jyotishka Mandal
AU  - Aryan Chaudhury
AU  - V. Sumitra
PY  - 2025
DA  - 2025/06/30
TI  - Performance Analysis of CNN-Based Indian Sign Language Recognition
BT  - Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
PB  - Atlantis Press
SP  - 15
EP  - 24
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-754-0_3
DO  - 10.2991/978-94-6463-754-0_3
ID  - Sharma2025
ER  -