Face Mask Detection using Convolutional Neural Networks

Amrit Singh; Chirag Wadhwa; Ritik Kedia; A. K. Madan

doi:https://doi.org/10.51976/ijari.922116

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Face Mask Detection using Convolutional Neural Networks

Amrit Singh, Chirag Wadhwa, Ritik Kedia, A. K. Madan

Vol 9 , Issue 2 , April - June 2021 | Pages: 103-107 | Research Paper

https://doi.org/10.51976/ijari.922116

Received: February 03, 2021 | Revised: March 28, 2021 | Accepted: April 05, 2021 | Published Online: June 15, 2021

Author Details ( * ) denotes Corresponding author

1. * Amrit Singh, Department of Mechanical Engineering, Delhi Technological University, Delhi, India (amrit1438@gmail.com)

2. Chirag Wadhwa, Department of Mechanical Engineering, Delhi Technological University, Delhi, India (chiragwadhwa23@gmail.com)

3. Ritik Kedia, Department of Mechanical Engineering, Delhi Technological University, Delhi, India (ritikkedia47@gmail.com)

4. A. K. Madan, Department of Mechanical Engineering, Delhi Technological University, Delhi, India (ashokmadan79@gmail.com)

COVID-19 pandemic has rapidly affected our day-to-day life disrupting the world trade and movements. Wearing a protective face mask has become a new normal. Soon, many public service providers will ask the customers to wear masks correctly to avail of their services. Therefore, face mask detection has become a crucial task to help global society. This paper presents a simplified approach to achieve this purpose using some basic Machine Learning packages like Tensor Flow, Keras, Open CV and Scikit-Learn. The proposed method detects the face from the image correctly and then identifies if it has a mask on it or not. As a surveillance task performer, it can also detect a face along with a mask in motion. The method attains accuracy up to 92.75%. We explore optimized values of parameters using the Sequential Convolutional Neural Network model to detect the presence of masks correctly.

Keywords

COVID-19; Face mask; Haar cascade; Tensor flow; Open CV; Raspberry PI

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