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Face recognition using 2DLDA algorithm
Author(s)
Kongsontana, Sittinon
Rangsanseri, Yuttapong
Date Issued
December 1, 2005
Type
Conference Paper
Abstract
This paper proposes Two-Dimensional Linear Discriminant Analysis (2DLDA) for feature extraction which used for face recognition application. This method is developed from Fisher Linear Discrimnant (FLD) and Two-Dimensional Principle Component Analysis (2DPCA). In this method, 2DLDA directly uses the image matrix to calculate the between-class scatter matrix and within-class scatter matrix. Moreover, 2DLDA will be handling the problem that the within-class scatter matrix maybe singular. The experimental results indicated that the 2DLDA method is more computationally efficient than conventional methods. © 2005 IEEE.
Citation
Proceedings 8th International Symposium on Signal Processing and Its Applications Isspa 2005, 2, 675-678, 2005
