Open AccessAutomated Social Distancing and Face Mask Detection System
Author(s) -
Onkar Madhavi,
Shivani Khente,
Sumit Kolipyaka,
Pallavi Chandratre
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.41530
Subject(s) - computer science , convolutional neural network , artificial intelligence , face (sociological concept) , executor , task (project management) , facial recognition system , computer vision , deep learning , face detection , covid-19 , machine learning , pattern recognition (psychology) , engineering , medicine , social science , disease , systems engineering , pathology , sociology , political science , infectious disease (medical specialty) , law
COVID-19 epidemic has fleetly affected our day-to- day life dismembering the world trade and movements. Wearing a defensive face mask has become a new normal. In the near future, numerous public service providers will ask the guests to wear masks rightly to benefit of their services. Thus, face mask recognition has turn out to be a pivotal task to help global society. This paper presents a simplified approach to achieve this purpose using some introductory Machine Learning packages like TensorFlow, Keras, OpenCV and Scikit- Learn. The projected system detects the face from the image appropriately and then identifies if it has a mask on it or not. As a surveillance task executor, it can also distinguish a face along with a mask in motion. The system attains precision up to95.77 and 94.58 independently on two different datasets. We discover optimized values of parameters using the Convolutional Neural Network model to spot the presence of masks rightly without causing over-fitting. Keywords: Coronavirus, Covid-19, Machine Learning, Face Mask Recognition, Convolutional Neural Network, TensorFlow