Face Appreciation Based Attendance System Using Haar cascade and Local Binary Pattern Histogram Algorithm
Author(s):
A Shakeela joy, A prabhu, L Gitson Tharmaraj, S.Ramesh, M.Subin Vijaya Balan, K.Ajay
Keywords:
Face recognition-based attendance system, Local Binary Pattern Histogram (LBPH), Euclidean distance value.
Abstract
The attendance system is used to track and keep an eye on a student's attendance in class. Attendance systems come in a variety of forms, including biometric-based, face recognition-based, radio frequency card-based, and conventional paper-based ones. The most time- and security-effective attendance system is one that uses face recognition. Numerous studies are conducted simply to examine students' recognition rates. This work focuses on a face recognition-based attendance system with the objective of reducing the false-positive rate by using a confidence threshold, or more specifically, a Euclidean distance value, while recognising unknown persons and saving their photographs. Local Binary Pattern Histogram (LBPH) algorithm is superior to other Euclidean distance-based techniques like Eigenfaces and Fisher faces. Due of their robustness, we employed the LBPH algorithm for face recognition and the Haar cascade for face detection. It can withstand monotone grayscale conversions. Our system is evaluated utilising scenarios like facial recognition rate, false-positive rate for that, and false-positive rate with and without employing a threshold in detecting unfamiliar persons. We discovered that college students' facial recognition rates are good, and their false-positive rates are very low. This technology can identify students even if they have grown beards or glasses. Unknown person face recognition is almost high, both with and without imposing a threshold value. While looking for unidentified people
Article Details
Unique Paper ID: 160965

Publication Volume & Issue: Volume 10, Issue 2

Page(s): 215 - 218
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