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Grade Differentiation Measure of Images

  • Maria Grzegorek
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 57)

Summary

This paper describes application of newly developed grade differentiation measure between two datasets to images processing. Pixels of an image are transformed into a dataset of records describing pixels. Each pixel is characterized by its gray level, gradient magnitude and a family of variables n 1,...,n k , where k has been arbitrarily chosen. Grade Correspondence Cluster Analysis procedure implemented in program GradeStat allows reorder a sequence of records and divides pixels onto similar groups/subimages. Procedure GCCA takes a significant amount of time in the case of large images. Comparison of grade differentiation measures between variables allows to decrease the number of variables and the same to decrease processing time.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Maria Grzegorek
    • 1
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarsawPoland

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