Real time image-based attendance system
Objective
A real-time image-based attendance system for educational settings utilizes pre-processed images from Google, employing Convolutional Neural Networks for accurate student identification and storing attendance details in Excel for efficient tracking.
Abstract
The Study proposed real-time image-based attendance system introduces an innovative approach to streamline attendance management in educational settings. By compiling a dedicated Students Dataset from non-live sources, specifically Google, and implementing pre-processing techniques like image resizing, the system ensures uniformity in image analysis. Employing the power of Deep Learning, particularly through Convolutional Neural Networks (CNNs), the system is trained on the collected dataset for accurate student identification. Notably, the same dataset is utilized for both training and testing phases, ensuring consistency in performance evaluation. Upon successful recognition, the system generates a classified text output containing student names and attendance details like time and date. This information is systematically stored in an Excel file, emphasizing the system's practicality for real-time student attendance tracking, combining precision, and efficiency through the integration of advanced Deep Learning technologies.
Keywords: Students Dataset, Pre
-Processing, Convolutional Neural Network, Deep learning and Accuracy.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
