Real Time Face Mask Detection-A Survey

G. Kale, Prashant Bhaware, R. Ingle, Sayali Sulbhewar, Yash Gugaliya, Mayur Kaware, P. Thakare
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引用次数: 2

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.
实时口罩检测——综述
新型冠状病毒肺炎全球大流行爆发后,对防护机制的需求日益迫切,口罩是首要防护机制。据世界卫生组织(who)介绍,新冠肺炎(covid -19)大流行正在引发全球健康大流行,在公共场所戴口罩是最成功的安全措施。卷积神经网络(cnn)已经发展成为图像识别模型的主导类别。本研究的目的是检查和测试机器学习能力,以检测和识别任何给定视频或图片中人们佩戴的口罩或实时口罩。本课题开发了一个基于gui的实时自动人脸检测与识别系统。它可以作为一种入口管理设备,通过对组织的员工或学生进行人脸登记,然后通过记录人脸照片来识别进出场所的个人。该方法利用了主成分分析(PCA)和HAAR级联算法。基于我们的模型的性能和准确性,二值分类器的结果将显示在人脸部分周围叠加一个绿色矩形,表示相机前的人戴着面具,或者显示一个红色矩形,表示相机前的人没有戴面具,同时显示该人的面部识别。人脸检测和人脸识别是当今非常重要的技术,而且我们注意到它们有各种各样的用途,如手机,军队用途,以及一些高风险的信息办公室。我们决定制作一种可以检测和识别人脸的设备,作为学生考勤系统,可以代替常规的纸质考勤系统和指纹考勤系统。我们项目的主要功能将使用LabVIEW来完成,因为LabVIEW是一个非常有用的编程工具,在面部使用和其他用途方面都非常有用。我们的项目是基于LabVIEW中的一个主程序,该程序可以检测和识别人脸并给出分数和参数,此外,子系统是一个与程序集成的Excel表格,以及一个消息传递设备,用于向缺席的学生或学生的家长发送消息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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