Face Recognition Using PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) Techniques

Abstract: image processing field is becoming more popular for the security purpose in now days. It has many sub fields and face recognition is one from them. Many techniques have been developed for the face recognition but in our work we just discussed two prevalent techniques PCA (Principal component analysis) and LDA (Linear Discriminant Analysis) and others in brief. These techniques mostly used in face recognition. PCA based on the eigenfaces or we can say reduce dimension by using covariance matrix and LDA based on linear Discriminant or scatter matrix. In our work we also compared the PCA and LDA.

Keywords: Face recognition, PCA, LDA, eigenvectors, eigenface.