Open AccessThe Attendance Marking System based on Eigenface Recognition using OpenCV and Python
Author(s) -
Khem Puthea,
Rudy Hartanto,
Risanuri Hidayat
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1551/1/012012
Subject(s) - python (programming language) , eigenface , computer science , facial recognition system , artificial intelligence , haar like features , attendance , face detection , computer vision , pattern recognition (psychology) , computer graphics (images) , operating system , economics , economic growth
Attendance of students in a large classroom is hard to be handled by the traditional system, as it is time-consuming and has a high probability of error during the process of inputting data into the computer. This paper proposed automated attendance marking system using face recognition technique. The system deployed Haar cascade to find the positive and negative of the face and eigenface algorithm for face recognition by using python programming and OpenCV library. The proposed method using PCA to resolved the problems such as lightning of the images, noise from the camera, and the direction of the student faces. The attendance of the student was updated to the Excel sheet after student’s face has been recognized.