Face recognition using a fusion method based on bidirectional 2DPCA

In this paper, we propose a face recognition method using a fusion method based on bidirectional 2DPCA. While the previous PCA method computes the covariance matrix by using a one-dimensional vector, 2DPCA method computes the covariance matrix by directly using a direct two-dimensional image, and extracts the feature vectors by solving an eigenvalue problem. The proposed method recognizes the faces by applying the modified 2DPCA obtaining a linear transformation matrix using two covariance matrices which are the row and column covariance matrices. The experimental results indicate that the proposed method shows a higher and more stable recognition rate than the conventional methods.