Exploring the Impact of Image Brightness on Sign Language Recognition Using Convolutional Neural Network

Jiawei Zhang

2024

Abstract

In order to enhance communication for the hard of hearing, sign language recognition technology is intended to understand sign language motions and convert them into text or voice. The primary goal of sign language recognition technology is to give deaf and normal individuals a means of communicating through signals that is both practical and efficient. Research on sign language identification is ongoing due to advancements in computer technology and the growing popularity of intelligence. Wearable input devices and Convolutional Neural Networks (CNN) are two major machine vision-based research methodologies used today. Strap-on input device-based sign language recognition has an advantage over machine vision-based recognition in that it can acquire real-time information on hand shape, finger flexion, and abduction. The research employs machine learning algorithms to analyze how variations in image brightness can affect the performance of CNNs in interpreting sign language gestures. The study adjusts brightness levels to assess how they impact recognition metrics such as accuracy, precision, recall, and F1 score. The findings suggest that variations in brightness have an impact on the models' accuracy of recognition.

Paper Citation

in Harvard Style

Zhang J. (2024). Exploring the Impact of Image Brightness on Sign Language Recognition Using Convolutional Neural Network. In Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM; ISBN 978-989-758-738-2, SciTePress, pages 229-233. DOI: 10.5220/0013296000004558

in Bibtex Style

@conference{mlscm24,
author={Jiawei Zhang},
title={Exploring the Impact of Image Brightness on Sign Language Recognition Using Convolutional Neural Network},
booktitle={Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM},
year={2024},
pages={229-233},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013296000004558},
isbn={978-989-758-738-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Modern Logistics and Supply Chain Management - Volume 1: MLSCM
TI - Exploring the Impact of Image Brightness on Sign Language Recognition Using Convolutional Neural Network
SN - 978-989-758-738-2
AU - Zhang J.
PY - 2024
SP - 229
EP - 233
DO - 10.5220/0013296000004558
PB - SciTePress