Texture analysis is used in a very broad range of fields and applications, from texture
classification (eg, for remote sensing) to segmentation (eg, in biomedical imaging), passing …

Complexity measures are important to understand and analyze systems with one
dimensional data. However, extension of these methods to images (two dimensional data) …

In this study, we propose to use a method based on the combination of sample entropy with
multiscale and multidimensional approaches, along with a fuzzy function. The model was …

Two-dimensional fuzzy entropy, dispersion entropy, and their multiscale extensions
(MFuzzyEn 2 D and MDispEn 2 D, respectively) have shown promising results for image …

Objective: We propose a new bidimensional entropy measure and its multiscale form and
evaluate their behavior using various synthetic and real images. The bidimensional …

Texture analysis is a subject of intensive focus in research due to its significant role in the
field of image processing. However, few studies focus on colored texture analysis and even …

As a nonlinear dynamic index, hierarchical permutation entropy (HPE) can effectively
represent the complexity change of time series. However, HPE only focuses on extracting …

Various walking speeds may induce different responses on the plantar pressure patterns.
Current methods used to analyze plantar pressure patterns are linear and ignore nonlinear …

Rolling bearing vibration signals with local failure usually contain rich fault characteristic in
the time and frequency domains. Two-dimensional multi-scale dispersion entropy (MDE 2D) …

Texture analysis is gaining popularity among the scientific community. A wide variety of
applications use texture analysis method. Texture analysis methods can be used for image …