Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4633122 | Applied Mathematics and Computation | 2008 | 7 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Young-Gil Kim, Young-Jun Song, Un-Dong Chang, Dong-Woo Kim, Tae-Sung Yun, Jae-Hyeong Ahn,