VGG-16-Based Framework for Identification of Facemask Using Video Forensics

ABSTRACT

In the context of the COVID-19 disease outbreak, organizations such as the universities are at risk of being essentially shut around the world if the overall condition does not improve. The other name for COVID-19 is a serious acute respiratory syndrome, a virus that causes serious respiratory problems. Corona virus-2 is a contagious agent spread through droplets in the air from an affected patient. This spreads easily by direct contact with affected patients or touching the objects which all already touched by the affected patients. Even if there are many vaccines available to defend against COVID-19 across the globe, still there is a high necessity to consider the precautions for avoiding infection. The major aspect for preventing the infection using a facemask that protects a person from entering the virus into the body through the nose and mouth of a person. The other major aspect for preventing the infection by washing hands using and washes or sanitizers. In the present article, the major and popular advanced technique used for image-based detection and classification is the Deep Learning-based VGG-16 technique. The deep learning technology is used in the analysis to identify face mask recognition and determine whether or not the individual is carrying a facemask. VGG-16 is the CNN (Convolutional Neural Network) framework is utilized for the present study. The Kaggle dataset considered consists of 25,000 images with each of the images having 225 × 225 pixels as the resolution, and the proposed model performed with a 96% accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.