Face attendance Recognition System using Machine Learning

Mini Project on
Submitted By:
MOHAMMED MUQEETH (161021733027)
SYED MUSHARAF AFZAL (161021733052)
MOHAMMED ABDUL RAOOF (161021733306)
Face Recognition Attendance
systems
Under the Guidance of:
MS.DR.FARHEEN SULTANA
Asst.Professor
CSE Department

Abstract
• The "Face Check-In" is an innovative web application designed to streamline the
attendance process by harnessing the power of face recognition technology. This system
leverages classification algorithms and Python libraries, such as face_recognition and
OpenCV-python, to accurately identify individuals and record their attendance in a hassle-
free manner.
• The core of the system is built upon the face_recognition library, enabling the application
to detect and recognize faces with exceptional accuracy. Combined with the
functionalities of OpenCV-python, which offers prebuilt functions for image processing,
the system efficiently processes incoming visual data, ensuring the seamless
identification of candidates.
• The web app is developed using the Streamlit library, providing a user-friendly interface
that facilitates easy access and management of attendance data. Upon login, candidates'
faces are captured and cross-referenced against a pre-registered database, associating
each individual with their name, roll number, date, and time of check-in.

Introduction/objective

• Our objective today is to introduce you to a cutting-
edge solution: face recognition attendance systems.

• We will explain how they work, highlight their benefits,
discuss data storage and implementation.
• and emphasize the importance of using this technology
for modern businesses and organizations.

•
•

Face Check-In is an attendance management system that uses facial recognition
algorithms to capture and analyze the unique facial features of individuals.
 The system maintains a database of pre-registered faces and compares them
with the face captured in real-time to identify and authenticate individuals.
And stores them in a CSV file.

Software and Hardware
Requirement
 Minimum 4GB RAM
 Intel Core i5 processor or better
 Python 3.7+
 Libraries :
Opencv-python.
Numpy.
Face-recognition
Streamlit.
Pickle
Pandas
 IDE : VS code.

System Analysis
• Existing system(Limitations):
• Manual entry error. Manual attendance systems rely
on humans to enter data, which can lead to errors.

• Time consuming. Taking attendance manually can be
time consuming especially in large organizations.

Drawbacks:
• Lack of analysis. Manual attendance systems don’t provide
analytics or insights into attendance patterns and trends.
• Difficulty to scale. As organizations grow manual attendance
system can be difficult to manage.
• Open to abuse. Manual attendance systems are also open
to abuse.

• Proposed System:
• Highly accurate. Face-based attendance systems are much
more accurate than manual attendance systems.
• This is because they use facial recognition technology
to identify employees, which is much more reliable than
human identification.

• Less prone to abuse. Face-based attendance systems are also
less prone to abuse than manual attendance systems.
• This is because it is difficult for employees to cheat the system by buddy-
punching or signing in for someone else.

• Efficient and easy to use. Face-based attendance systems
are very efficient and easy to use.
• Employees simply need to scan their faces in order to clock in
and out, which can save them a lot of time.

• Scalable. Face-based attendance systems are very scalable, which
means that they can be easily used by large organizations.
• This is because they do not require any manual data entry,
which can save a lot of time and resources.

Activity Diagrams
Activity diagram
for attendance
Activity diagram
for adding new
student

Applications
• Can be used in offices, colleges or any organizations to
ease the attendance process.
• Used for security system and anamoly detection in cctv
cameras

Reference Bibliography References
• https://github.com/ageitgey/face_recognition
• https://www.youtube.com/watch?v=BYCKvM8eZGA&t=2782s
• https://www.researchgate.net/publication/
341876647_Face_Recognition_based_Attendance_Management_
System
• https://ieeexplore.ieee.org/document/9215441
• https://www.ijert.org/research/face-recognition-based-attendance-
system-IJERTV9IS060615.pdf

Face attendance Recognition System using Machine Learning

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