International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022
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p-ISSN: 2395-0072
FACE MASK DETECTION USING MACHINE LEARNING AND IMAGE PROCESSING Siya Kamat1, Akshata Karapurkar2,Rinki Matonkar3 ,Sanat Shirodkar4, Rajesh Gauns5,Diksha Prabhu Khorjuvenkar6 1,2,3,4 Department of Computer Engineering Agnel Institute of Technology and Design, Assagao, Goa 5,6 Assistant Professor, Department of Computer Engineering Agnel Institute of Technology and Design, Assagao, Goa ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Abstract - In light of the current COVID-19
with a soap or a disinfectant containing at least 60% alcohol (in the absence of soap and water), avoiding direct contact with an infected person. It's also important to avoid using unwashed hands to contact the mouth, nose, or eyes.
pandemic, many public places require that individuals wear face masks. However, few individuals don't consider it necessary. People use different excuses not to use a mask whenever in public areas and it is not always possible for the authorities to monitor whether people are wearing face masks or not. This is where machine learning-based facemask detection can be helpful.
Utilizing face masks is the most crucial step in stopping the spread of sickness. However, some people don't think it's necessary and give various justifications for not wearing a mask when in public places. Using image processing and machine learning, it is possible to identify people's faces and divide them into two groups: those who are wearing masks and those who are not.
Through machine learning, face-mask detection can be carried out to automatically determine if a face mask is being worn by someone or not. This can be achieved by utilizing a camera or a webcam to take a static image or video of the person.
2. LITERATURE SURVEY
With the help of this project, we will be able to detect whether or not a person is wearing a mask in both a static image and a real-time stream. This project can be used at the entrance of public places like shops, hospitals, banks, schools, colleges, malls, airports, etc. as a digital scanning tool. This will lessen human mistakes and instantly notify those without masks. Firstly, a dataset will be prepared to consist of 2 classes; with-mask and without-mask. A machine learning model shall be created and trained with the dataset gathered. After the training is completed, the model shall be assessed with a different dataset. Machine learning techniques will be used for classifying the detected people into the with-mask or without-mask category.
2.1 Face Mask Detection using MTCNN Vansh Gupta and Rajeev Rajput developed the face mask detection system using MTCNN. The pattern of wearing face covers openly is ascending because of the COVID-19 pestilence everywhere in the world. People used to wear coverings before Covid-19 to protect their health from air pollution. The suggested model in their work can be combined with observation cameras to prevent COVID-19 transmission by allowing the identification of people who are not wearing facial coverings but are using veils.[1]
Key Words: Machine Learning, Image Processing, Face Mask Detection, MTCNN, EfficientNet, MobileNet
2.1.1 Machine Learning (ML) In general, Machine Learning is the study of algorithms that can automatically improve given more data. It is often seen as part of AI since these algorithms can often make decisions without being specifically programmed to do so. They learn from data, building a model that allows them to make predictions or decisions.[1]
1. INTRODUCTION Coronaviruses are a large family of viruses that infect humans, other mammals, and birds. These viruses can cause several respiratory, gastrointestinal, and neurological diseases. COVID-19 is a disease caused by a coronavirus, and its effects can possibly range from mild to fatality.
2.1.2 Image Processing Image processing is a method of manipulating an image to either enhance it or extrapolate knowledgeable data from it. It's a form of signal processing where the input is an image and the output can be either another image or characteristics/features related to that image.
At times of a pandemic, the best prevention is to avoid contracting the virus. A few things one should follow are when coughing and sneezing covered with tissue which is then safely disposed of. Next, cleanse your hands routinely
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