MULTIFRAC: An ImageJ plugin for multiscale characterization of 2D and 3D stack images

Abstract

MULTIFRAC is an ImageJ plugin that addresses, through a user-friendly interface, the characterization and multiscaling analysis of 2D and 3D binary and gray images. It is notably recommended for the study of complex void structure and scaling behavior in soil science as well as for the analysis of self-similar patterns in any segmented phase. The main features of MULTIFRAC include multifractal analysis implementing box counting and gliding box methodologies, fractal dimension estimation, lacunarity characterization, characteristic length and configuration entropy analysis. It has been extensively tested with real and synthetic CT-images and the conclusions were published in high impact factor journals. In this paper, we detail and reference the algorithms implemented, describe its features and give some illustrative examples.

Keywords

• Multifractal
• Lacunarity
• Configuration entropy
• ImageJ