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In this paper, we have compared use of PCA (Principal components analysis) with two powerful feature extraction techniques LDA (Linear discriminant analysis) GDA (Generalized discriminant analysis) which have already been used in palmprint verification. For testing purpose 10 colorful whole-hand images of each hand of 43 persons are collected by a digital camera, namely, a small dataset of 860 images...
Canonical Correlation Analysis (CCA) is a standard tool in statistical analysis that measures the linear relationship between two data sets. In this paper, we present a multibiometric approach which combines palmprint feature and finger geometry feature based on Canonical Correlation Analysis. First, we use linear discriminant analysis (LDA) to build the palmprint feature. Second, the geometry feature...
This paper presents a novel palmprint recognition approach based on generalized discriminant analysis (GDA). The method uses GDA to extract palmprint features for palmprint recognition. GDA project palmprint images from a high-dimensional input space to a lower dimensional feature space, in which the palmprints from the different palms can be discriminated much more efficiently. The experiment results...
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