A note on fractal sets and the measurement of fractal dimension
Konrad Sandau
Physica A: Statistical Mechanics and its Applications, 1996, vol. 233, issue 1, 1-18
Abstract:
The fractal dimension of a set in the Euclidean n-space may depend on the applied concept of fractal dimension. Several concepts are considered here, and in a first part, properties are given for sets such that they have the same fractal dimension for all concepts. In particular, self-similar sets hold these properties. The second part deals with the measurement of fractal dimension. An often-used method to empirically compute the fractal dimension of a set E is the box-counting method where the slope of a regression line gives the estimate of the fractal dimension. A new interpretation, which concentrates on the visible complexity of the set, uses counted boxes to define generators for adjacent self-similar sets. Their maximal fractal dimension is assigned to the set as a measurement of fractal dimension or of visible complexity. The results from the first part guarantee that all measurements are independent of the considered concepts. The construction suggests a new method, which is called extended box-counting method, to estimate fractal dimension or to measure complexity of an image in a given range of magnification. The method works without linear regression and has the advantage to nearly preserve the union stability (maximum property).
Keywords: Box counting method; Fractal sets; Hausdorff dimension; Metric dimension; Maximum property (search for similar items in EconPapers)
Date: 1996
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437196002488
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:233:y:1996:i:1:p:1-18
DOI: 10.1016/S0378-4371(96)00248-8
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().