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Higuchi Dimension of Digital Images

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  • Helmut Ahammer

Abstract

There exist several methods for calculating the fractal dimension of objects represented as 2D digital images. For example, Box counting, Minkowski dilation or Fourier analysis can be employed. However, there appear to be some limitations. It is not possible to calculate only the fractal dimension of an irregular region of interest in an image or to perform the calculations in a particular direction along a line on an arbitrary angle through the image. The calculations must be made for the whole image. In this paper, a new method to overcome these limitations is proposed. 2D images are appropriately prepared in order to apply 1D signal analyses, originally developed to investigate nonlinear time series. The Higuchi dimension of these 1D signals is calculated using Higuchi's algorithm, and it is shown that both regions of interests and directional dependencies can be evaluated independently of the whole picture. A thorough validation of the proposed technique and a comparison of the new method to the Fourier dimension, a common two dimensional method for digital images, are given. The main result is that Higuchi's algorithm allows a direction dependent as well as direction independent analysis. Actual values for the fractal dimensions are reliable and an effective treatment of regions of interests is possible. Moreover, the proposed method is not restricted to Higuchi's algorithm, as any 1D method of analysis, can be applied.

Suggested Citation

  • Helmut Ahammer, 2011. "Higuchi Dimension of Digital Images," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-8, September.
  • Handle: RePEc:plo:pone00:0024796
    DOI: 10.1371/journal.pone.0024796
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    Cited by:

    1. Klonowski, W. & Pierzchalski, M. & Stepien, P. & Stepien, R. & Sedivy, R. & Ahammer, H., 2013. "Application of Higuchi’s fractal dimension in analysis of images of Anal Intraepithelial Neoplasia," Chaos, Solitons & Fractals, Elsevier, vol. 48(C), pages 54-60.
    2. Philipp Kainz & Michael Mayrhofer-Reinhartshuber & Helmut Ahammer, 2015. "IQM: An Extensible and Portable Open Source Application for Image and Signal Analysis in Java," PLOS ONE, Public Library of Science, vol. 10(1), pages 1-28, January.

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