Abstract
In this paper, a new feature representation technique called 2-directional 2-dimensional direct linear discriminant analysis ((2D)2 DLDA) is proposed. In the case of face recognition, the small sample size problem and need for many coeffficients are often encountered. In order to solve these problems, the proposed method uses the direct LDA and two directional image scatter matrix. The ORL face database is used to evaluate the performance of the proposed method. The experimental results show that the proposed method obtains better recognition rate and requires lesser memory than the direct LDA.
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© 2006 Springer-Verlag Berlin Heidelberg
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Cho, Du., Chang, Ud., Kim, Kd., Kim, Bh., Lee, Sh. (2006). (2D)2 DLDA for Efficient Face Recognition. In: Chang, LW., Lie, WN. (eds) Advances in Image and Video Technology. PSIVT 2006. Lecture Notes in Computer Science, vol 4319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949534_31
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DOI: https://doi.org/10.1007/11949534_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68297-4
Online ISBN: 978-3-540-68298-1
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