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An Algorithm To Minimize Within-Class Scatter And To Reduce Common Matrix Dimension For Image Recognition, Ümi̇t Çi̇ğdem Turhal, Alpaslan Duysak
An Algorithm To Minimize Within-Class Scatter And To Reduce Common Matrix Dimension For Image Recognition, Ümi̇t Çi̇ğdem Turhal, Alpaslan Duysak
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a new algorithm using 2DPCA and Gram-Schmidt Orthogonalization Procedure for recognition of face images is proposed. The algorithm consists of two parts. In the first part, a common feature matrix is obtained; and in the second part, the dimension of the common feature matrix is reduced. Resulting common feature matrix with reduced dimension is used for face recognition. Column and row covariance matrices are obtained by applying 2DPCA on the column and row vectors of images, respectively. The algorithm then applies eigenvalue-eigenvector decomposition to each of these two covariance matrices. Total scatter maximization is achieved taking the …