This document describes a face recognition attendance system created by students. The system aims to create a convenient self-powered portable smart attendance system using face recognition technology. It includes a database to store facial images of students and can identify if a face matches one in the database, notifying the teacher of the student's attendance status. Some key advantages are reduced costs, easy reporting and integration. The system was implemented and initial results showed new student enrollments and image uploads were successful.

1. By
Tushar Bhootra
(PB35-1032201153)
Pratham Palresha
(PB57-1032202039)
Mohammad
(PB5-1032202079)
FACE RECOGNITION ATTENDANCE
SYSTEM
School of Electronics and Communication Engineering
MIT World Peace University, Pune

2. CONTENTS:
 Introduction
 Aim and Objectives
 Block Diagram
 Explanation
 Implementation
 Results
 Application
 Key Learning
 Conclusion
 References
School of Electronics and Communication Engineering
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3. INTRODUCTION:
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i. Face Recognition is a biometric
method that uses a person's saved
record and live capture or digital
picture data to identify them.
ii. The Attendance Management
System with Face Recognition was
created for tracking daily student
attendance at schools, universities,
and institutes.
iii. A growing number of industries,
including security, research,
automation, and many more, are
utilising face recognition
technology.
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4. AIM AND OBJECTIVES:
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i. To create a convenient, self-powered portable smart
attendance system
ii. Publish the faces of new employees or pupils in the
database.
iii. Establish a database for the attendance tracking
system.
iv. Have adequate memory to hold the database.
v. Capable of letting the user know whether or not the
face-recognition operation was successful.
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5. BLOCK DIAGRAM
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6. EXPLANATION:
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Our master processor has two inputs, one from the camera which is real time
data and another from pre- stored image data. Initially when camera sends
input to master processor the face detection algorithm starts functioning. The
face detection algorithm is designed in such a way that it will only crop the
facial section of input image. This facial section is identified with help of
matching coordinates like eyes, nose and mouth which works as reference
while cropping as image.
Later this facial section of image is been stored in form of face registration. As
we know each face has its own identity in form of dedicated eyes pattern, nose
and mouth figure, by considering this our algorithm tags each input face with
different labels. Simultaneously master processor is also carrying out another
process which feature extraction of pre- stored image. Now this extracted
features goes under machine learning stage where machine learns which face
belongs to which particular tag or label. By using this parameter both inputs
are compared in classifier and if the features matches within particular
threshold value then algorithm indicates that face is been identified, later by
selecting desired data such as name, serial number and status of that identity
is transmits the information via IOT to another computer which is assumed
to be facultys computer. This is how we get real time attendance.

7. IMPLEMENTATION
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8. RESULTS
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The enrolment of the new student can be done in
this stage. The images of the students are uploaded
successfully.

9. School of Electronics and
Communication Engineering
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10. APPLICATION:
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An attendance management system can keep track of
employee working hours, time-off, break time, login-time,
departures, students’ attendance etc. The system not only
keeps an accurate track of presence and absence but also
reduces the time and cost the HR team and office staff
spend on attendance management activities. The system
also maintains an accurate record of the student
attendance and offers timely summaries. Teachers can
simply mark attendance in just a tap. It reduces the extra
effort required to mark the attendance manually. The fast
and accurate system also avoids incorrect and duplicate
data entry. You can create attendance reports at a click of
a button.

11. ADVANTAGES
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Communication Engineering
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1. Cost Reduction
2. Easy reporting
3. Easy integration
4. Leave Management Visibility
5. Reduced Administrative Load
6. Improved Productivity
DIS-ADVANTAGES:
1. Requires maintenance
2. Needs power supply to work

12. KEY LEARNINGS
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i. The first is usage of Haar Features for the detection of
features in the input image.
ii. The second is the introduction of a new image illustration
called the - Integral Image which allows the features used by
our detector to be computed very quickly.
iii. The third is an easy and efficient classifier which is built using
the AdaBoost learning algorithm to select a small number of
critical visual features from a very large set of potential
features.
iv. The fourth contribution is a process for combining classifiers
in a-cascade which allows background regions of the image to
be quickly discarded while spending more computation on
promising face-like regions.
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13. CONCLUSION:
School of Electronics and Communication Engineering
I. The popularity of face recognition attendance systems is
further increased by the speed of image processing and
simplicity of integration.
II. An automatic attendance management system is a necessary
tool for any learning management schools colleges kr
companies . Most of the existing systems are time consuming
and require a semi manual work from the teacher or students.
Our approach aims to solve the issues by integrating face
recognition in the process. Even though this system has
disadvantages like detecting large number of faces, there is
much more room for improvement. Since we implement a
modular approach we can improve different modules until we
reach an acceptable detection and identification rate. The
system can be enhanced in such a way that the accuracy,
detection rate and recognition rate can be increased so that
more number of students can be detected and recognized for
those who are present in the class.
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14. REFERENCES:
School of Electronics and Communication Engineering
 https://www.analyticsvidhya.com/blog/2021/11/build-
face-recognition-attendance-system-using-python/
 https://www.questjournals.org/jses/papers/Vol5-issue-
2/D05021829.pdf
 https://www.trume.in/face-recognition-attendance-
system-in-
india/#:~:text=truMe's%20Face%20Recognition%20Att
endance%20System,increasing%20their%20productivity
%20and%20efficiency.
 https://www.secureye.com/product-cat/face-biometric-
attendance-system/
 https://machinelearningprojects.net/face-recognition-
based-attendance-system/
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15. Thank-You!!!
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