Face recognition using assembled matrix distance metric based 2DLDA algorithm

Linear discriminant analysis (LDA) is a well-known method for face recognition in feature extraction and dimension reduction. As a new scheme, two-dimensional linear discriminant analysis (2DLDA) has been used for face recognition recently. In this paper, an assembled matrix distance metric based 2DLDA is proposed for face representation and recognition. In this new method, an assembled matrix distance (AMD) metric is used to measure the distance between two 2DLDA feature matrices. To test this new method, ORL face database is used and the results show that the assembled matrix distance metric based 2DLDA method outperforms the 2DLDA method and achieves higher classification accuracy than the 2DLDA algorithm