A Multi-Camera Automated Attendance System Using LBPH-Based Face Recognition

Authors:
  • NHNelson Habumugisha
    Nelson Habumugisha
  • JNJonathan Ngugi
    Jonathan Ngugi
  • DSDjuma Sumbiri
    Djuma Sumbiri
Open Access
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Abstract
This study presents the development and evaluation of a Multi-Camera Automated Attendance System employing Local Binary Patterns Histograms (LBPH) for face recognition. Traditional single-camera solutions struggle in large classrooms with occlusion, lighting variability, and limited viewpoints. All these challenges are addressed by the Multi-Camera Automated Attendance System Using LBPH-Based Face Recognition (MCAAS-LBPH). This system integrates three IP cameras with LBPH and Haar Cascade Classifier algorithms to achieve real-time, accurate student identification. It provides daily reporting and stores attendance in Comma Separated Value (CSV) format for quick conversion to Excel or PDF.