Krzysztof Kucharski

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The complete theory for Fisher and dual discriminant analysis is presented as the background of the novel algorithms. LDA is found as composition of projection onto the singular sub-space for within-class normalised data with the projection onto the singular subspace for between-class normalised data. The dual LDA consists of those projections applied in(More)
Linear Discriminant Analysis (LDA) is widely known feature extraction technique that aims at creating a feature set of enhanced discriminatory power. It was addressed by many researchers and proved to be especially successful approach in face recognition. The authors introduced a novel approach Dual LDA (DLDA) and proposed an efficient SVD-based(More)
A cascade of linear and nonlinear operators is designed for facial image indexing and recognition. We show that such an approach results in efficient and low-dimensional feature space for face representation with enhanced discriminatory power. Experimental evaluation of the proposed FR algorithm was conducted on MPEG test set with over 8000 images of about(More)
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