Real Time Face Mask Detection-A Survey

https://doi.org/10.55529/ijitc21.1.4

Authors

  • Gargi Kale Bachelor Of Engineering (Scholar), Department of Computer Engineering Jagadambha College of Engineering and Technology, Yavatmal
  • Prashant Bhaware Bachelor Of Engineering (Scholar), Department of Computer Engineering Jagadambha College of Engineering and Technology, Yavatmal
  • Rohit Ingle Bachelor Of Engineering (Scholar), Department of Computer Engineering Jagadambha College of Engineering and Technology, Yavatmal
  • Sayali Sulbhewar Bachelor Of Engineering (Scholar), Department of Computer Engineering Jagadambha College of Engineering and Technology, Yavatmal
  • Yash Gugaliya Bachelor Of Engineering (Scholar), Department of Computer Engineering Jagadambha College of Engineering and Technology, Yavatmal
  • Mayur Kaware Bachelor Of Engineering (Scholar), Department of Computer Engineering Jagadambha College of Engineering and Technology, Yavatmal
  • Parag Thakare Bachelor Of Engineering (Scholar), Department of Computer Engineering Jagadambha College of Engineering and Technology, Yavatmal

Keywords:

Open CV,Haar Cascade,ANN,Convolution,VGG-16,Max-pooling 2D,SQL,Tkinter.

Abstract

After the breakout of the worldwide pandemic COVID-19, there arises a severe need of protection mechanisms, face mask being the primary one. According to the World Health Organization, the corona virusCOVID-19 pandemic is causing a global health epidemic, and the most successful safety measure is wearing a face mask in public places. Convolutional Neural Networks (CNNs) have developed themselves as a dominant class of image recognition models. The aim of this research is to examine and test machine learning capabilities for detecting and recognize face masks worn by people in any given video or picture or in real time. This project develops a real-time, GUI-based automatic Face detection and recognition system. It can be used as an entry management device by registering an organization’s employees or students with their faces, and then recognizing individuals when they approach or leave the premises by recording their photographs with faces.The proposed methodology makes uses of Principal Component Analysis (PCA) and HAAR Cascade Algorithm. Based on the performance and accuracy of our model, the result of the binary classifier will be indicated showing a green rectangle superimposed around the section of the face indicating that the person at the camera is wearing a mask, or a red rectangle indicating that the person on camera is not wearing a mask along with face identification of the person. Face detection and face recognition are very important technologies these days, furthermore we noticed that they got have a variety of uses such as cellphones, army uses, and some high risk information offices. We decided to make a device that detects and recognize the face as a student attendance system and can be a substitute for the regular paper attendance system and finger print attendance system. The main function in our project is going to be done using LabVIEW because, LabVIEW is a very helpful programming tool in regards of facial uses and very helpful in other uses. Our project is based on a main program in LabVIEW that detects and recognize faces with giving scores and parameters, furthermore the subsystems are an Excel sheet that is integrated with the program, and a messaging device that is for either a message for absent students or to the student’s parent.

Published

2021-12-25

How to Cite

Gargi Kale, Prashant Bhaware, Rohit Ingle, Sayali Sulbhewar, Yash Gugaliya, Mayur Kaware, & Parag Thakare. (2021). Real Time Face Mask Detection-A Survey. International Journal of Information Technology & Computer Engineering , 2(01), 1–4. https://doi.org/10.55529/ijitc21.1.4

Issue

Section

Aricle Publication