A Face Recognition Based Biometric Solution in Education

Abstract

In last years, several biometric modalities are coming back into the field of education. Especially, face recognition modality that allows authenticating humans based on their facial features. The main objective of this paper is to implement the recognition system part for a global software that is intended to be used in many applications related to the educational field. Therefore, we propose to combine the face description method based on Local Gradient Probabilistic Pattern (LGPP), the two dimensional subspace methods, and machine learning classifiers. Firstly, we extract principal face component using the LGPP descriptor. Then, 2DDWT, 2DPCA, and 2DLDA subspace methods were implemented to reduce face features. Finally, support vector machine (SVM) and artificial neural network (ANN) based machine learning algorithms are applied to classify the set of the final features vectors. The experimental results on relevant databases demonstrate the effectiveness of the proposed system.