Student class attendance record plays an important role in most of the universities of Asia particularly countries like India. Keeping this in mind, an efficient attendance management system is proposed in this paper. This system makes use of dimensionality reduction using PCA-based face recognition algorithm incorporating Euclidean distance as the distance classifier. Faces of the students are segmented using Viola–Jones algorithm. Based on the recognized faces, attendance is updated into an Excel database. The algorithm has been tested using two different student databases. Training database is created using 50 subjects including male and female with different facial variations (15 instances per subject). Statistical data shows that an accuracy of the algorithm is greater than 99% with normal lighting conditions.

Mariyam Milofa

Papers

Dimensionality Reduction Using Principal Component Analysis for Lecture Attendance Management System