Skip to main navigation Skip to search Skip to main content

Mask Detection Algorithm for Public Places Entering Management During COVID-19 Epidemic Situation

  • Harbin Institute of Technology
  • University of Oulu
  • Ministry of Public Security of the People's Republic of China

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

COVID-19 now is spreading fast all over the world. Wearing masks has proven to be an effective way to prevent COVID-19 to some extent. This paper studies a mask detection algorithm for public places entering management during COVID-19 epidemic situation. Only people wearing masks are allowed to enter. Cameras are fixed at the entrances of public places and take photos of people who are coming in. Then, a series of pre-processing are performed, including face detection, normalization, etc. Residual network is used as the classifier. Simulation results show that the average recognition accuracy can reach 90%.

Original languageEnglish
Title of host publicationCommunications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems
EditorsQilian Liang, Wei Wang, Xin Liu, Zhenyu Na, Xiaoxia Li, Baoju Zhang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages414-419
Number of pages6
ISBN (Print)9789811584107
DOIs
StatePublished - 2021
Event9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020 - Changbaishan, China
Duration: 4 Jul 20205 Jul 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume654 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020
Country/TerritoryChina
CityChangbaishan
Period4/07/205/07/20

Keywords

  • Face detection
  • Image processing
  • Mask detection
  • ResNet

Fingerprint

Dive into the research topics of 'Mask Detection Algorithm for Public Places Entering Management During COVID-19 Epidemic Situation'. Together they form a unique fingerprint.

Cite this