Proceedings of the 7th International Conference on Applied Engineering (ICAE 2024)

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Finger Recognition Detection System Using Mediapipe as Communication Solution for People with Disabilities

Authors
M. Wahyu Elfander1, Ryan Satria Wijaya1, *
1Politeknik Negeri Batam, Batam, Riau Island, 29461, Indonesia
*Corresponding author. Email: ryan@polibatam.ac.id
Corresponding Author
Ryan Satria Wijaya
Available Online 25 December 2024.
DOI
10.2991/978-94-6463-620-8_11How to use a DOI?
Keywords
Sign Language; Confusion Matrix; Artificial Neural Network
Abstract

Sign language is a language used by people with disabilities, especially the deaf and mute to communicate. The problem is, not everyone can understand sign language. This study aims to create a system that can translate sign language. The system can also produce sound with the text to voice method. The system is built using Mediapipe to detect fingers that form sign language. The system performs classification by combining 2 machine learning models with the Artificial Neural Network (ANN) method. The first model is used to classify letters A-Z and the second model is used to classify movement patterns in letters J and Z. The accuracy of the first model is 94% and the accuracy of the second model is 95%. The model will also be evaluated using the confusion matrix technique to find recall, f1-score, and precision of 25 letters or classes.

Copyright
© 2024 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 7th International Conference on Applied Engineering (ICAE 2024)
Series
Advances in Engineering Research
Publication Date
25 December 2024
ISBN
978-94-6463-620-8
ISSN
2352-5401
DOI
10.2991/978-94-6463-620-8_11How to use a DOI?
Copyright
© 2024 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  - M. Wahyu Elfander
AU  - Ryan Satria Wijaya
PY  - 2024
DA  - 2024/12/25
TI  - Finger Recognition Detection System Using Mediapipe as Communication Solution for People with Disabilities
BT  - Proceedings of the  7th International Conference on Applied Engineering (ICAE 2024)
PB  - Atlantis Press
SP  - 139
EP  - 149
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-620-8_11
DO  - 10.2991/978-94-6463-620-8_11
ID  - Elfander2024
ER  -