Nonlinear dimensionality reduction method with the use of reference nodes for analysis of digital image collections

Authors:
E. V. Myasnikov
Affiliations:
Institute of Image Processing Systems, Russian Academy of Sciences, Samara, Russia 443110
Venue:
Pattern Recognition and Image Analysis
Year:
2011

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Abstract

This method is based on hierarchical clusterization of data in a multidimensional space and the Sammon mapping. The key feature of the dimensionality reduction stage is the use of reference node lists created by the results of the hierarchical clusterization stage. The experimental results given in this work include the method performance quality estimates for some systems of the features extracted from digital image collections of different sizes.