Vignesh H, Suresh J, N. Lalithamani

Proceedings of the 26th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2022, Vol. III, pp. 95-100 (2022); https://doi.org/10.54808/WMSCI2022.03.95

Vignesh H
Department of Computer Science and Engineering, Amrita School of Computing, Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore, India

Suresh J
Department of Computer Science and Engineering, Amrita School of Computing, Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore, India

N. Lalithamani
Department of Computer Science and Engineering, Amrita School of Computing, Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore, India

Cite this paper as:
H, V., J, S., Lalithamani, N. (2022). Mask Detection for Life Protection. In N. Callaos, J. Horne, B. Sánchez, M. Savoie (Eds.), Proceedings of the 26th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2022, Vol. III, pp. 95-100. International Institute of Informatics and Cybernetics. https://doi.org/10.54808/WMSCI2022.03.95

“Health is Wealth” such a wealth of people is being affected and they are put to death on deathbeds in millions by a newly discovered virus called n-CoV (Corona virus). Covid is so-called mysterious because people affected by this disease are asymptotic. This infectious disease is mostly transmitted through droplets when an infected person coughs or sneezes. One of the main precautions that everyone must follow is wearing a mask. Some people wear masks improperly whenever they visit crowded places where there are high chances of this disease being spread. We have designed a real-time face mask detector that aims at detecting masks worn by people to reduce the transmission of this virus and make people wear masks in crowded areas. We can install this system at the entrance of places where there is more number of crowds. The detector follows Convolutional Neural Network (CNN), a part of Deep-Learning used to analyse visual imagery. It takes an input image, assigns importance (learnable weights and biases) to various aspects/objects of the image, and differentiates one from the other. Cascade Classifier detects the frontal face. Results have shown the detector classifies people with and without masks at an accuracy of 96.97%.