Face recognition system based on principal component analysis and support vector machine classification

Abstract

Principal component analysis is a commonly used feature extraction technology in face recognition. It can reduce the dimension of data while trying to retain the characteristics of the original data. Face images can be reduced in dimension through principal component analysis, which can effectively reduce the number of features and simplify the model, the complexity. The application of support vector machines in face recognition is based on its powerful classification ability that can effectively find decision boundaries in feature space and distinguish different categories (i.e. faces of different people). Based on the respective advantages of principal component analysis and support vector machine, this article will discuss a face recognition method based on a combination of principal component analysis and support vector machine support vector machine method, and implement the system through MATLAB.