An Integrated Computer Vision Pipeline for Face-Based Attendance: Detection, Recognition and Secure Logging
Year: 2025
Type: article
Abstract: Smart, reliable attendance is crucial for modern organizations.Manual systems leftover time and invite fraud.Reliable attendance systems changed administrative costs and enhance accountability.Automation lets staff emphasis on essential tasks.We established a Face Recognition Based Attendance System (FRBAS) that progresses accuracy, effectiveness, and security over traditional approaches.Using Haarcascade for face detection and a Local Phase Quantization with Histogram Bin (LPBH) feature extraction, the system trains on up to 100 images per person to shape robust patterns.FRBAS systematizes attendance recording, avoids proxy fraud, decreases human error, and empowers real-time monitoring.We also inspect technical, ethical, and privacy challenges and propose strategies for responsible placement.
Authors: Shahid Hussain, Hashmat Ullah, Shah Zeb, Abbas Khan
Institutions: Xi'an Jiaotong University, Islamia College University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7083306202
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