A new direct LDA (D-LDA) algorithm for feature extraction in face recognition

The problem of determining the optimal set of discriminant vectors for feature extraction in pattern recognition is investigated. We propose a new direct LDA (D-LDA) method that is applicable to small sample size (SSS) problems often arising in face recognition. The experimental results on two popular databases show the effectiveness of the proposed method.

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