Face Mask Detection Using Feature Extraction

Usha, K.; Mahathi, Devarakonda; Shravya, Pillarisetti

doi:10.1007/978-981-16-0081-4_46

Cited by 1 publication

(1 citation statement)

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“…The mask detection system by Kamale Usha et al, uses the Viola-Jones algorithm to detect whether a person is using a mask or not and the correct position of the mask or not. This system helps in screening so that it can provide security at work or in public places [9]. Another example, a system to monitor the use of masks with the intention of enforcing COVID-19 health protocols by Fathul A. L., et al If a user is not wearing a mask, the system has an auditory feature that acts as a warning.…”

Section: Introductionmentioning

confidence: 99%

Design of Smart Door Lock System Using Face Recognition and Mask Detection Based on Viola-Jones Algorithm with Android Integration

Nurindini

Swacaesar²,

Astika³

et al. 2023

Jartel

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Indonesia has been affected by COVID-19 since 2020. In order to stop the virus spreading, the government puts Large Scale Social Restrictions. There is no denying that during this pandemic, criminality is increasing, and this is due to nothing other than the need to survive. The stealing and invading of homes is one of the crimes that have increased. Additionally, the government has strengthened health procedures to require that individuals wear masks while doing activities outside. A system that can identify faces and identify the use of masks was developed in order to solve this issue. Face recognition is used to increase security, and mask detection systems work to enforce the wearing of masks when engaging in outside activities. Both of these technologies can be combined into a single smart door lock system for the home. The system will apply facial recognition identification when someone wants to enter the house and mask detection when they want to do activities outside the house. As a monitoring tool, data will be delivered in the form of an image via the user's Android. This is proven by the accuracy rates of facial identification of 95% and mask detection of 97.5% in this research.

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Section: Introductionmentioning

confidence: 99%