1. INTERNSHIP SEMINAR
On
“Student Face Recognition Attendance System”
Carried out at
Mitra Software PVT. LTD, Shivamogga
during
25.08.2022 TO 25.09.2022
National Education Society ®
JNN College of Engineering
Sawalanga Road, Navule, Shivamogga -277204
(Accredited by NBA, NAAC 'B' & Certified by UGC 2f & 12B)
Department of Electronics & Telecommunication Engineering
Presented by:
Apoorva R V
4JN19ET006
Internal Guide:
Prof. Madhusudhan G.
Assistant Professor,
Dept of ETE
JNNCE , Shivamogga
External Guide:
Mr. Suraj Gowda
Managing director
Mitra Software
2. Contents
About the Company/organization where internship was carried
Area of Internship
Details of Software and hardware knowledge acquired
Introduction of the project undertaken
Aim of project undertaken
Theoretical background
Design and Implementation details
Flowchart
Results & Discussion
Conclusion
Outcome of the internship
Certificate
References
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3. About the Company/organization
• Mitra Software’s established in the year 2013 at Machenahalli
Shivamogga.
• It designs and develops the software’s for educational, hospitality,
institutions and companies.
• Mitra software’s design android apps as per the needs of the
customers.
• Listed under top 100 software’s companies awarded by Alva's Pragati.
• Provided service for more than 300+ business entities within.
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4. Area of Internship
Machine learning (ML):
• A branch of artificial intelligence, concerned with the design and
development of algorithms that allow computers to evolve behaviors
based on empirical data.
• As intelligence requires knowledge, it is necessary for the computers
to acquire knowledge.
• Training is the process of making the system able to learns
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5. Software Requirements
Anaconda:
Anaconda is an open-source distribution of the Python and R
programming languages for data science that aims to simplify package
management and deployment.
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6. Introduction of the project
• Student Face Recognition Attendance system is a software developed
for daily attendance in schools, colleges and institution.
• It facilitates to access the attendance information of a particular student
in a particular class.
• This system will also help in evaluating attendance eligibility criteria
of a student.
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7. Aim of project
To identify and verify a person using the person's facial features
and automatically mark attendance.
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8. Theoretical background
• The human face is a unique representation of individual identity.
• We receive information through the image projected into our eyes, by
specifically retina in the form of light.
• Identification of an individual is performed by comparing real-time
capture image with stored images in the database of that person
• system which required the administrator to locate eyes, ears, nose
and mouth from images.
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9. Design and Implementation details
• In this project we used OpenCV module integrated with Python
• Create a DATASET of the student by entering his ID Number
• Train the dataset, Training Image file is created.
• A picture of the class is taken, and the RECOGNIZER python file is
initiated.
• Attendance is taken by cropping the faces in the picture and
comparing with the faces in the database and status saved in the
EXCEL fiIe.
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10. Flowchart
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Capture
the faces
Face
Recognition
Face
detection
If face in
database
Face
database
Attendance
database
Take
Attendance
Exist
Unknown
faces
save
Yes
No
Save
Check
camera
12. Conclusion
• System has been envisioned for the purpose of reducing the errors
that occur in the traditional (manual) attendance taking system.
• Proposed algorithm is capable of detect multiple faces, and
performance of system has acceptable good results.
• The efficient and accurate method of attendance that can replace the
old manual methods.
• The aim is to automate and make a system that is useful to the
organization such as an institute
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13. Outcome of the internship
• I learn a lot about skills, and strengths and weaknesses.
• This can come in the form of valuable input from supervisors or from
colleagues.
• One of the most valuable skills you will gain from an internship is the
ability to speak with people in a professional setting.
• Discussions with bosses or coworkers are different from discussions
with lecturers or fellow students.
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15. References
[1] Journal of Software Engineering and Simulation Volume 5 ~ Issue 2 (2019)
[2] A brief history of Facial Recognition, NEC, New Zealand,26 May 2020.
[3] Face detection, TechTarget Network, Corinne Bernstein, Feb, 2020.
[4] Face Detection with Haar Cascade, Towards Data Science-727f68dafd08,
Girija Shankar Behera, India, Dec 24, 2020.
[5] Face Recognition: Understanding LBPH Algorithm, Towards Data
Science90ec258c3d6b, Kelvin Salton do Prado, Nov 11, 2017.
[6] What is Facial Recognition and how sinister is it, The guardian, Ian
Sample, July, 2019.
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