Biometric Authentication using Face Recognition Algorithms for A Class Attendance System
Keywords:
Biometric authentication, feature extraction methods, face recognition algorithms, attendance systemAbstract
The paper is about developing an attendance system that is based on a biometric
verification technique using a face recognition method that is expected able to avoid system
manipulation in comparison to other attendance systems. Face recognition algorithm
consists of two parts, namely, the training and testing components. The main focus of the
study is on the feature extraction method in which the study proposes a face recognition
algorithm using three types of features extraction methods which are the local binary
pattern (LBP), principle component analysis (PCA) and histogram of oriented gradient
(HOG) along with support vector machine (SVM) algorithm as the classifier. The
performance analysis of each algorithm was carried out by testing the algorithms using
multiple styles of facial images. The styles of the facial images are the frontal face, angled
face, expression face and also low light illumination face images. The results show that the
HOG+SVM algorithm obtained the highest accuracy in every test. Furthermore, it is also
found that the HOG+SVM method can execute the recognition process efficiently and fast.
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