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A comparative example between the use of PCA and MDS for image classification

Abstract:

In this paper, a practical comparison is performed between the use of the principal component analysis method (PCA) and the multidimensional scaling method (MDS) for image classification applications, where the images under study are contaminated using different tools. Here, characteristics of these images are obtained and, according to criteria for measuring the distance between the images, their classification is carried out. For the case under study, it can be said that the classification using PCA performed better than the classification using MDS.