Real-Time Detection of Face Mask Using Convolutional Neural Network

  • Imam Husni Al Amin Universitas Stikubank
  • Deva Ega Marinda Universitas Stikubank
  • Edy Winarno Universitas Stikubank
  • Dewi Handayani U.N Universitas Stikubank
  • Veronica Lusiana Universitas Stikubank
DOI: https://doi.org/10.29207/resti.v7i3.5036
Keywords: Mask detection; CNN; face detection; face recognition; pollution

Abstract

Masks are a simple barrier that can help us prevent transmission and spread of disease from other people who enter the body, avoid exposure to air pollution, and protect the face from the adverse effects of sunlight. However, many people are still ignorant about the importance of wearing masks for health. This study aims to detect whether or not to use masks in real-time by proposing a deep learning model to reduce illness and death caused by air pollution. The convolutional Neural Network (CNN) method was used in this research to detect facial recognition using a mask and not using a mask. The public dataset used in this research consists of 1300 images with 650 data using masks and 650 data without masks. The results of this study show that the proposed CNN method works well in detecting masked and non-masked faces in real time. The proposed method obtains an accuracy value of 97.5% at epoch 50. Previous research on mask detection using the Eigenface method yielded an accuracy of 88.89%, and another study using the Viola-Jones method yielded an accuracy of 95.5%. It can be concluded that this research can increase the accuracy value of previous studies. So, this research is feasible to be applied to the detection of mask use in real time.

 

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Published
2023-06-03
How to Cite
Imam Husni Al Amin, Deva Ega Marinda, Edy Winarno, Dewi Handayani U.N, & Veronica Lusiana. (2023). Real-Time Detection of Face Mask Using Convolutional Neural Network. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 7(3), 697 - 704. https://doi.org/10.29207/resti.v7i3.5036
Issue
Vol 7 No 3 (2023): June 2023
Section
Information Technology Articles

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