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http://dx.doi.org/10.5391/JKIIS.2009.19.5.648

Bilateral Diagonal 2DLDA Method for Human Face Recognition  

Kim, Young-Gil (충북대학교 전자정보대학 영상통신연구실)
Song, Young-Jun (충북대학교 충북BIT연구중심대학육성사업단)
Kim, Dong-Woo ((주) 이씨엠)
Ahn, Jae-Hyeong (충북대학교 전자정보대학 영상통신연구실)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.19, no.5, 2009 , pp. 648-654 More about this Journal
Abstract
In this paper, a method called bilateral diagonal 2DLDA is proposed for face recognition. Two methods called Dia2DPCA and Dia2DLDA were suggested to reserve the correlations between the variations in the rows and columns of diagonal images. However, these methods work in the row direction of these images. A row-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the column variation of alternative diagonal face images. In addition, column-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the row variation in diagonal images. A bilateral projection scheme was applied using left and right multiplying projection matrices. As a result, the dimension of the feature matrix and computation time can be reduced. Experiments carried out on an ORL face database show that the proposed method with three different distance measures, namely, Frobenius, Yang and AMD, is more accurate than some methods, such as 2DPCA, B2DPCA, 2DLDA, etc.
Keywords
Linear discriminant analysis(LDA); 2DLDA; Diagonal 2DLDA; Face recognition;
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