Face Mask Detection System

Computer Science and Engineering

Efficient strategies to contain the Corona virus Disease- 2019 (COVID-19) or any pandemic in general, are peremptory to relieve the negatively impacted public health and global economy, with the full scope yet to unfold. In the absence of highly effective drugs and abundant medical resources, many measures are taken to manage the infection rate and avoid the depletion of limited hospital resources. Wearing masks is among the non-pharmaceutical intervention (NPI) measures that could be effectively implemented at a minimum cost and without dramatically disrupting social practices. Therefore, it is essential to develop a model that detects the citizens who wear a face mask and those who do not at public places like malls, hospitals, airports, etcetera in order to allow entry only to those people wearing masks to ensure the well-being of other people present. The system proposes a CNN model developed using Machine Learning and Deep Learning techniques that detect people wearing masks in an image or live video stream and allow entry only to those people as face masks are part of an infection control strategy to eliminate cross-contamination.

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