Face Recognition Based Automated Attendance Management System using Principal Component Analysis

Aalam Gumber, Navneet Kaur

Abstract: Security and verification of a person is a crucial part of any industry. One of the commonly used technique for this purpose is face recognition. Face recognition is an effective means of authenticating a person. The advantage of this approach is that, it enables us to detect changes in the face pattern of an individual to an appreciable extent. There are several approaches to face recognition of which Principal Component Analysis (PCA) has been used extensively in literature. In this paper, Face Recognition based Automatic Attendance Management System using Principle Component Analysis is proposed. The system consists of a database of a set of facial patterns for each individual. The characteristic features called -eigenfaces- are extracted from the stored images using which the system is trained for subsequent recognition of new images.

Keywords: Biometrics, Face Recognition, Principal Component Analysis, Eigen Values, Eigen Vector

How to Cite?: Aalam Gumber, Navneet Kaur, "Face Recognition Based Automated Attendance Management System using Principal Component Analysis", Volume 4 Issue 6, June 2015, International Journal of Science and Research (IJSR), Pages: 971-975, https://www.ijsr.net/getabstract.php?paperid=SUB155274, DOI: https://dx.doi.org/10.21275/SUB155274