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A nonlinear method for dimensionality reduction of data using reference nodes

  • Representation, Processing, Analysis, and Understanding of Images
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Abstract

A nonlinear method for dimensionality reduction based on the hierarchical clusterization of data and the Sammon mapping is proposed in the work. An essential element is the use of lists of reference nodes created based on the results of the hierarchical clusterization of data in the original multidimensional space in the dimensionality reduction. The work quality of the proposed method has been analyzed for a number of feature systems extracted from digital images, as well as for collections of images of various volumes.

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Authors and Affiliations

  1. Image Processing Systems Institute of the Russian Academy of Sciences, Molodogvardeiskaya 151, Samara, 443001, Russia

    E. V. Myasnikov

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  1. E. V. Myasnikov
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Correspondence to E. V. Myasnikov.

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Evgenii Valer’evich Myasnikov. Born 1981. Graduated cum laude from Samara State Aerospace University (SSAU) in 2004 with a specialization in Automated Systems of Information Processing and Control. Received candidate’s degree in 2007. Docent of the Chair of Geoinformatics of SSAU and scientific researcher of the Laboratory of Mathematical Methods of Image Processing of the Image Processing Systems Institute of the Russian Academy of Sciences. Author of 40 papers, coauthor of a monograph. Scientific interests: pattern recognition, image processing, geoinformatics, software design and development. Member of the Russian Association of Pattern Recognition and Image Analysis.

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Myasnikov, E.V. A nonlinear method for dimensionality reduction of data using reference nodes. Pattern Recognit. Image Anal. 22, 337–345 (2012). https://doi.org/10.1134/S1054661812020101

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