International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI-Enabled Real-Time Face Recognition Attendance System Using Flask and OpenCV |
|---|---|
| ABSTRACT | Attendance management that needs to be ensured in various educational institutions is mainly based on very inefficient and fraudulent methods of roll calls, and signature sheets along with radio frequency identification (RFID) cards. In this paper, we introduce a lightweight real-time Computer Vision-based Face recognition-based student attendance system which is developed using free and open-source technologies such as Flask, OpenCV, and SQLite database. This elaborative system makes use of Haar-cascade classifiers for face detections and proposes hybrid measures of similarity counting template matching, histogram correlation, and structural similarity estimation to become more efficient and accurate in its recognition. The developed application stores individual students' facial features along with automatic marks generation using template matching from real-time videos for the concerned student. This application will be a much efficient harness of economics after optimising its computing power and thus lead to individual student and faculty interfaces. The manuscript will demonstrate experiments aimed at verification of efficiency and accuracy of the proposed method under different lighting conditions. |
| AUTHOR | PRIYANKA G V, PRAJWAL V, SHARATH G J, SAGAR T R, MANOJ MARUTHI GUDI Department of Computer Science and Engineering, Jain Institute of Technology, Davangere, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312112 |
| pdf/112_AI-Enabled Real-Time Face Recognition Attendance System Using Flask and OpenCV.pdf | |
| KEYWORDS | |
| References | 1. Smitha, P. S. H., & Afshin. “Face Recognition based Attendance Management System,” International Journal of Engineering Research & Technology (IJERT), vol. 09, no. 05, May 2020. 2. AI-Driven Attendance Tracking with Haar Cascade and ResNet, Procedia Computer Science, vol. 258, 2025. 3. Ishaq, K., & Bibi, S., “IoT Based Smart Attendance System Using RFID: A Systematic Literature Review,” Aug. 2023. 4. Kuang & Baul, “Real-time attendance system with FaceNet and Haar Cascade,” 5. Nurmalasari, R. R., et al., “Face Recognition Based Attendance System Using Haar Cascade with Histogram Equalization,” Jurnal Pendidikan Multimedia, 2023. 6. T. Venkata Subbamma et al., “Face Recognition System using OpenCV,” IJRASET Research Paper (2025). 7. AI-Driven Attendance Tracking with deep learning combinations, Procedia Computer Science, 2025 |
