Statistical analysis of digital images of periodic fibrous structures using generalized Hurst exponent distributions

Tomasz Blachowicz, Andrea Ehrmann and Krzysztof Domino

Physica A: Statistical Mechanics and its Applications, 2016, vol. 452, issue C, 167-177

Abstract: Distinction of diverse two-dimensional periodic structures can be based on a large number of methods and parameters, while the quantitative description of differences between similar samples is usually difficult. This article aims, by the use of statistical random walk in a generalized q-order dimensional space, at introducing a methodology to qualify the networked structures on the basis of exemplary textile samples. The presented results were obtained at 1-bit monochromatic maps obtained from optical microscopic pictures. Significant features of samples were represented by the obtained distributions of Hurst exponents and Shannon entropy calculations.

Keywords: Random walk; Hurst exponent; Statistical analysis; Image analysis; Shannon entropy; Textile materials (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437116001795
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:452:y:2016:i:c:p:167-177

DOI: 10.1016/j.physa.2016.02.013

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 ().