BENOIT 1.3

BENOIT™ is a computer program that enables you to measure the fractal dimension and/or hurst exponent of your data sets using your choice of eleven methods:

  • ruler, box, information, perimeter-area, and mass for analysis of self-similar patterns (2D data);
  • R/S, power-spectral analysis, variogram, roughness-length, and wavelets for analysis of self-affine traces (1D data);
  • fragmentation for size-frequency data (1D data).

Filtering is provided in the program to permit removal of white noise from your trace using either Fourier or Wavelet techniques. The user can also generate synthetic self-affine traces using a built-in trace generator with tuning parameters.

A user friendly, visual interface makes BENOIT™ a research and study tool for anyone interested in fractal properties of their data sets. You are just a few clicks away from the results of the analysis. BENOIT™ automatically calculates default values for various tuning parameters or you can control the performance of each method by manual tuning the parameters. Interactive data plots allow you to deactivate data points outside of the fractal range to increase accuracy. For those interested in how each method works, which method(s) are preferable for a given data set, and further information about fractal methods and their properties, an extensive help file is built into the program that explores these and other fractal-related topics.

 

BENOIT for Matlab 1.0

BENOIT for Matlab is a fractal analysis package for Matlab 6.5 or higher that enables you to measure the fractal dimension and/or hurst exponent of your data sets using your choice of ten methods:

  • 3D box counting for 3D self-similar objects (3D data);
  • ruler, box, information, perimeter-area, and mass for analysis of self-similar patterns (2D data);
  • R/S, power-spectral analysis, variogram and roughness-length for analysis of self-affine traces (1D data).

 

 




Platform requirements

BENOIT 1.3: Microsoft Windows 95/98/Me/NT/2000/XP/Vista/7

BENOIT for Matlab 1.0: Microsoft Windows 95/98/Me/NT/2000/XP/Vista/7, Matlab 6.5 (or higher) and Signal Processing and Image Processing Toolboxes

 

Input data formats

1D traces and size-frequency data: text format or MS-Excel format.

2D patterns: BMP files (color or black and white). The program automatically converts your color files to black and white.

3D objects (available only in BENOIT for Matlab): BMP files. 3D object should be represented as a number of 2D 'slices'.


 

Screen shots Methods for estimation of Fractal Dimension of self-similar patterns


Methods for estimation of Hurst Exponent and Fractal Dimension of self-affine traces