2. INTRODUCTION
This project is designed so as to automate the traditional attendance system where attendance is
marked manually.
This project involves building an attendance system which utilizes facial recognition to mark the
presence, time-in, and time-out of employees.
Face Recognition software is a convenient and highly accurate security tool.
Facial Recognition is safer as there are no passwords for hackers to compromise.
The proposed system will save time by automating the attendance process,
eliminating the needed for manual entry or barcode scanning.
3. SYSTEM SPECIFICATION
HARDWARE CONFIGURATION
Processor : Intel(R) Core (TM) i5-5200U
Memory : 4.00 GB RAM
Hard disk : 900 GB
Keyboard : 104 keys standard keyboard
SOFTWARE CONFIGURATION
Software : PYCHARM
Operating system : Windows 10 Pro
Front End : PYTHON
Back End : SQLITE
Technology : OPENCV
Framework : DJANGO
4. FRONT END - PYTHON
Python is a high-level, programming language that is designed to be easy to read
and write.
It is an open source
It is an interpreted language
Free to download
It is a cross-platform language
Python's libraries are often used to develop machine learning and AI applications.
Python is an ideal language for prototyping and testing new ideas quickly.
5. SQLite is a relational database management system that is designed to be embedded into other
applications.
SQLite databases are stored in a single file, making them easy to distribute and backup.
It is a lightweight and self-contained database engine that requires no separate server process
and no configuration.
SQLite is a cross-platform database engine that can be used on Windows, macOS, Linux, and
many other platforms.
There are many APIs and drivers available for SQLite in different programming languages,
including C/C++, Java, Python, and PHP.
6. 1. OpenCV: OpenCV is an open-source computer vision library that provides a range of tools and
algorithms for image processing and computer vision tasks. It can be used for face detection, alignment,
and recognition in attendance systems.
2. DLib: DLib is a C++ library that provides a range of tools and algorithms for machine learning, image
processing, and computer vision tasks. It includes a face recognition module that can be used to train and
recognize faces in attendance systems.
3. Face Recognition: Face Recognition is a Python library that provides a simple interface for face
recognition tasks. It uses deep learning algorithms to detect and recognize faces in attendance systems.
4. Scikit-learn: Scikit-learn is a popular machine learning library that provides a range of tools and
algorithms for classification and regression tasks. It can be used to train and evaluate classifiers for face
recognition in attendance systems.
OPEN CV
7. WORKING OF
MODULES
The project consists of twos main modules. They are :-
1. ADMIN MODULE
2. EMPLOYEE MODULE
ADMIN MODULE:-
This module mainly deals with the management of the
employee’s profile. Admin can see the report of each employee, employee
can see his/her attendance report along with some possible filters such as
filter by employee and filter by date.
EMPLOYEE MODULE:-
This module mainly deals with the functionalities related to the
employees of the organization. Using the following features provided in
this module employees can log into the system using their credentials.
18. ADVANTAGES
Accuracy: The face recognition technology used in the proposed system is highly accurate,
reducing the chances of errors in attendance records.
Scalable: The proposed system can be easily scaled to accommodate a large number of
users, making it ideal for use in schools, colleges, and workplaces.
Security: The proposed system offers enhanced security features by verifying the identity
of students or employees, preventing unauthorized access.
Time-saving: The proposed system will save time by automating the attendance process,
eliminating the need for manual entry or barcode scanning.
19. DISADVANTAGES
REQUIRES A LOT OF SPACE TO STORE TRAINING DATA SET
FOR ACCURACY.
THE SYSTEM DOES NOT MARK LATE ATTENDANCE RECORD.
THE SYSTEM NEEDS TO BE UPDATED REGULARLY WHENEVER
NECESSARY.
20. FUTURE
ENHANCEMENT
The system can be made more efficient by adding a feature that marks absent automatically if the
employee is not on time.
A feature can be added where an employee is automatically sent a warning if his attendance or
working hours are below the threshold.
The number of training images can be reduced so that less storage is required. This can be done by
removing duplicate images of the same person, or images with similar embeddings.
The training time can be reduced by retraining the classifier only for the newly added images.
Wrongly classified images can be added to the training dataset with the correct label so as to
increase the accuracy of the recognition model.
21. CONCLUSION
Facial recognition is becoming more prominent in our society. It has made major progress in the
field of security. These systems are currently associated with many top companies and industries
thus adapting to the fast-growing technologies.
The website is designed to stay up to date by giving administrators the ability to access each and
every employee’s attendance records.
This technology can be further developed to be used in other avenues such as ATMs, accessing
confidential files, or other sensitive materials.
It is a very effective tool that can help law enforcers to recognize criminals and software
companies in leveraging the technology to help users in accessing them.
