Haar-VGG: Face Attendance System

Attendance taking is a crucial practice in educational institutions in Malaysia, but the traditional manual method is time-consuming and risky, particularly in the post-Covid era.To address this, a face recognition attendance system using Python is developed.The Viola-Jones algorithm known as Haar is utilized for face detection, and transfer learning on VGGFace is applied for model training, using 195 images from FLW dataset and volunteers among students.The system achieves a validation and testing accuracy of 1.0 through image preprocessing and augmentation.The attendance system includes a user-friendly graphical interface and live webcam feed, enabling instant recognition and recording of attendance.Integration with a MySQL database allows easy access to attendance records for teachers.This advanced system saves time, reduces the risk of virus transmission, and simplifies attendance management, offering a convenient and efficient solution for educational institutions.

Authors

Publication Details

Journal
International Journal of Integrated Engineering
Published
2025-07-18
DOI
https://doi.org/10.30880/ijie.2025.17.02.020
Citations
1
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
1.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Haar-VGG: Face Attendance System

Raja Abdullah Raja Ahmad, Mohd Wafi Nasrudin, Zair Asrar Ahmad, Ahmad Ashraf Abdul Halim et al.
1 citations
International Journal of Integrated Engineering
Face recognition and analysis
1.28
article

Haar-VGG: Face Attendance System

Raja Abdullah Raja Ahmad, Mohd Wafi Nasrudin, Zair Asrar Ahmad, Ahmad Ashraf Abdul Halim, Muhammad Imran Ahmad, Quah Xuan Ying
article en
1 citations

Abstract

Attendance taking is a crucial practice in educational institutions in Malaysia, but the traditional manual method is time-consuming and risky, particularly in the post-Covid era.To address this, a face recognition attendance system using Python is developed.The Viola-Jones algorithm known as Haar is utilized for face detection, and transfer learning on VGGFace is applied for model training, using 195 images from FLW dataset and volunteers among students.The system achieves a validation and testing accuracy of 1.0 through image preprocessing and augmentation.The attendance system includes a user-friendly graphical interface and live webcam feed, enabling instant recognition and recording of attendance.Integration with a MySQL database allows easy access to attendance records for teachers.This advanced system saves time, reduces the risk of virus transmission, and simplifies attendance management, offering a convenient and efficient solution for educational institutions.

International Journal of Integrated EngineeringVol. 17(2)
Openalex Percentile: Top 15%
Face recognition and analysis
1.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Haar-VGG: Face Attendance System — Raja Abdullah Raja Ahmad, Mohd Wafi Nasrudin, et al. · International Journal of Integrated Engineering (2025) | TGRS Research Map | TGRS