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Face Mask Detection

EasyChair Preprint no. 6013

5 pagesDate: July 6, 2021

Abstract

Face recognition is of the most interesting modal of biometric. Due to its low interfering nature and to the constant decrease in image acquisition cost, it’s particularly suitable for a wide number of real time applications. At this paper we are proposing a very fast image pre- processing by the introduction of a linearly shaded elliptical mask at the canter over our faces.
COVID-19 pandemic caused by the virus name coronavirus is continuously spreading until now to the various parts of the world. The impact of COVID19 have seen almost all sectors of development. The healthcare system is going through a crisis. Several precautions are measured had been taken to reduce the spread of this disease where wearing a mask is one of them. We propose a system that restrict the growth of COVID-19 by its feature of finding out people who are not wearing any facial mask in a smart city network where all the public places are monitored with CCTV cameras. When a person without a mask is detected, Automatic the corresponding authority is informed through the city network.

Keyphrases: deep learning, machine learning, OpenCV

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:6013,
  author = {Prateek Choudhary and Syed Osama and Lakshya Jaiswal},
  title = {Face Mask Detection},
  howpublished = {EasyChair Preprint no. 6013},

  year = {EasyChair, 2021}}
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