Face mask detection

1. Face Mask
Detection
Presented By:
SANDEEP C S MY.SC.U3BCA20024
PRAMOD C MY.SC.U3BCA20030
THEJAS GOWDA MY.SC.U3BCA20038
SRUJAN R S MY.SC.U3BCA20046
Project Supervisor
NAVYA K S
Faculty Associate
Department of Computer Science

2. Introduction To Broad Area:
Due to COVID, wearing a face mask is must in order to stay safe. As the country starts going through various
stages of reopening ,face masks have become an important element of our daily lives to stay safe.Wearing face
mask will be required in order to socialize or conduct business. So, this application utilizes a camera to detect if a
person is wearing a mask or not. The 209th report of the world health organization (WHO) published on 16th
August 2020 reported that coronavirus disease (COVID-19) caused by acute respiratory syndrome (SARS-CoV2)
has globally infected more than 6 Million people and caused over 379,941 deaths worldwide . According to
Carissa F. Etienne, Director, Pan American Health Organization (PAHO), the key to control COVID-19 pandemic
is to maintain social distancing, improving surveillance and strengthening health systems . Recently, a study on
understanding measures to tackle COVID-19 pandemic carried by the researchers at the University of Edinburgh
reveals that wearing a face mask or other covering over the nose and mouth cuts the risk of Coronavirus spread
by avoiding forward distance travelled by a person’s exhaled breath by more than 90% . Steffen et al. also carried
an exhaustive study to compute the community-wide impact of mask use in general public, a portion of which
may be asymptomatically infectious in New York and Washington. The findings reveal that near universal
adoption (80%) of even weak masks (20% effective) could prevent 17–45% of projected deaths over two months in
New Work and reduces the peak daily death rate by 34–58% . Their results strongly recommend the use of the face
masks in general public to curtail the spread of Coronavirus. Further, with the reopening of countries from
COVID-19 lockdown, Government and Public health agencies are recommending face mask as essential measures
to keep us safe when venturing into public. To mandate the use of facemask, it becomes essential to devise some
technique that enforce individuals to apply a mask before exposure to public places.

3. Introduction to specific area:
The purpose of the project “Face Mask Detection” is to create a tool that identifies the image of a human that can
calculate the probability that he/she wearing a mask or not in public places. During COVID, wearing a face mask was
compulsory in order to stop the spread of flu and now mask is must in order to stay safe for ourself. As the country under
went through various stages of reopening of lockdowns and became liberal on COVID protocols, face masks have
become an important element of our daily lives to stay safe. Wearing face masks will be required in order to socialize or
conduct business. So, this application utilizes a camera to detect if a person is wearing a mask or not.

4. Problem Definition :
The purpose of the project “Face Mask Detection” is to create a tool that identifies the image of a human that can
calculate the probability that he/she wearing a mask or not in public places. This application utilizes a camera to
detect if a person is wearing a mask or not.

5. Objectives Of the Project:
The main objectives of Face Mask Detection In Public are :
 People wear face masks once they step out of their homes and authorities strictly ensure that people are
wearing face masks while they are in groups and public places.
 To monitor that people are following this basic safety principle, a strategy should be developed. A face mask
detector system can be implemented to check this.
 To monitor that people are following this basic safety principle, a strategy should be developed. A face mask
detector system can be implemented to check this.
 Face detection is one of the applications of object detection and can be used in many areas like security,
biometrics, law enforcement and more. There are many detector systems developed around the world and
being implemented. However, all this science needs optimization; a better, more precise detector, because
the world cannot afford any more increase in corona cases.

6. Scope Of The Project :
• The main scope of the project is to detect people wearing masks or not in public places .
• This helps in automatic detection of people restricting them from entering into public places
without masks.
• Due to this technology the human intervention to fine/alert people can be reduced.

7. LITERATURE SURVEY:
3-DFace Recognition Under Occlusion Using Masked Projection
Authors: : Alyuz, B. Gokberk, and L. Akarun Year: 2013
With advances in sensor technology, the three-dimensional (3-D) face has become an emerging biometric modality,
preferred especially in high security applications. However, dealing with occlusions covering the facial surface is a
great challenge, which should be handled to enable applicability to fully automatic security systems. In this paper,
we propose a fully automatic 3-D face recognition system which is robust to occlusions. We basically consider two
problems: 1) occlusion handling for surface registration, and 2) missing data handling for classification based on
subspace analysis techniques. For the alignment problem, we employ an adaptively-selected- model-based
registration scheme, where a face model is selected for an occluded face such that only the valid nonoccluded
patches are utilized. After registering to the model, occlusions are detected and removed. In the classification
stage, a masking strategy, which we call masked projection, is proposed to enable the use of subspace analysis
techniques with incomplete data. Furthermore, a regional scheme suitable for occlusion handling is incorporated
in classification to improve the overall results. Experimental results on two databases with realistic facial
occlusions, namely, the Bosphorus and the UMB-DB, are reported. Experimental results confirm that registration
based on the adaptively selected model together with the masked subspace analysis classification offer an
occlusion robust face recognition system.

8. System architecture of the Proposed System:

9. DFD:

10. The year 2020 has shown mankind some mind-boggling series of events amongst which the
COVID-19 pandemic is the most life changing event which has startled the world since the year
began. Affecting the health and lives of masses, COVID-19 has called for strict measures to be
followed in order to prevent the spread of disease. From the very basic hygiene standards to the
treatments in the hospitals, people are doing all they can for their own and the society’s safety; face
masks are one of the personal protective equipment. People wear face masks once they step out of
their homes and authorities strictly ensure that people are wearing face masks while they are in
groups and public places. In the existing system the people face is detected by the surveillance
cameras. As it becomes complex in nature. It only detects the faces but the masked face needs to be
recognized manually. The maintenance is high for monitoring the surveillance cameras.
Existing System:

11. To overcome the drawbacks of the existing system, the proposed system has been evolved. This projects aim is
to monitor that people are following the basic safety principles. This is done by developing a face mask
detector system. People have to cover their faces in public, supermarkets, public transports, offices, and stores.
Retail companies often use software to count the number of people entering their stores. They may also like to
measure impressions on digital displays and promotional screens. We are planning to improve our Face Mask
Detection tool and release it as an open-source project. Our software can be equated to any existing USB, IP
cameras, and CCTV cameras to detect people without a mask. This detection live video feed can be
implemented in web and desktop applications so that the operator can see notice messages . Software operators
can also get an image in case someone is not wearing a mask. Furthermore, an alarm system can also be
implemented to sound a beep when someone without a mask enters the area. This software can also be
connected to the entrance gates and only people wearing face masks can come in.
Proposed System:

12. Work done so far:

13. References:
 www.google.com
 https://www.geeksforgeeks.org/face-detection-using-
python-and-opencv-with-webcam/