Fractal and Multifractal Analysis in Environmental, Medical and Technical Fields: Pattern Recognition, Analysis and Processing of Images

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Life Science, Biophysics".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1714

Special Issue Editors


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Guest Editor
Amazonian Materials Group, Department of Physics, Federal University of Amapá, Macapá 68903-419, Brazil
Interests: fractal analysis; fractal features; image processing; surface physical biotechnology; materials science; surface architecture; monofractal and multifractal approach; 3D spatial analysis
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Guest Editor
Division of Technologies, Federal University of Alagoa, Delmiro Gouveia 57480-000, Brazil
Interests: statistical physics and its interdisciplinary applications
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Guest Editor
Department of Physics, Federal University of Sergipe, São Cristóvão 49100-000, Brazil
Interests: solid surfaces; interfaces and thin films; nanomaterials; material characterization; magnetism
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Special Issue Information

Dear Colleagues,

Pattern recognition techniques applied to image processing and analysis have continually evolved over the years, mainly due to the significant increase in studies involving mathematical morphology, neural networks and image analysis systems based on machine learning. Texture analysis, for example, has been extensively employed for automatic pattern recognition in images, as an alternative to human cognitive capacity. The application of this technique directly benefits areas such as control theory, manufacturing, biomedicine and taxonomy, among others. In this context, the use of fractal descriptors, such as fractal dimension, succolarity, lacunarity and the multifractal spectrum, deserve attention because they can appropriately measure complex shapes, particularly those found in nature. Considering this, we encourage our colleagues to contribute to our multidisciplinary Special Issue.

The aim of this Special Issue is to advance research on topics relating to Fractal and Multifractal Analysis in Environmental, Medical and Technical Fields: Pattern Recognition, Analysis and Processing of Images. Potential topics include (but are not limited to) the following:

  • Fractal and/or multifractal analysis of images using scanning probe microscopy (SPM);
  • fractal and/or multifractal analysis of images using scanning and/or transmission electron microscopy;
  • pattern recognition using fractal descriptors in medical images;
  • pattern recognition using fractal descriptors in images of environmental interest;
  • fractal descriptors combined with neural networks;
  • mathematical morphology and fractal descriptors;
  • fractal descriptors and machine learning.

Dr. Erveton Pinheiro Pinto
Dr. Marcelo Amanajás Pires
Dr. Nilson dos Santos Ferreira
Guest Editors

Manuscript Submission Information

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Keywords

  • fractal analysis
  • multifractal spectrum
  • lacunarity spectrum
  • pattern recognition
  • neural networks
  • mathematical morphology
  • machine learning
  • medical images
  • nature textures
  • surfaces
  • scanning probe microscopy (SPM)
  • transmission electron microscopy (TEM)
  • scanning electron microscopy (SEM)

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Published Papers (1 paper)

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Review

15 pages, 5564 KiB  
Review
Morphological Features of Mathematical and Real-World Fractals: A Survey
by Miguel Patiño-Ortiz, Julián Patiño-Ortiz, Miguel Ángel Martínez-Cruz, Fernando René Esquivel-Patiño and Alexander S. Balankin
Fractal Fract. 2024, 8(8), 440; https://doi.org/10.3390/fractalfract8080440 - 26 Jul 2024
Cited by 1 | Viewed by 1025
Abstract
The aim of this review paper is to survey the fractal morphology of scale-invariant patterns. We are particularly focusing on the scale and conformal invariance, as well as on the fractal non-uniformity (multifractality), inhomogeneity (lacunarity), and anisotropy (succolarity). We argue that these features [...] Read more.
The aim of this review paper is to survey the fractal morphology of scale-invariant patterns. We are particularly focusing on the scale and conformal invariance, as well as on the fractal non-uniformity (multifractality), inhomogeneity (lacunarity), and anisotropy (succolarity). We argue that these features can be properly quantified by the following six adimensional numbers: the fractal (e.g., similarity, box-counting, or Assouad) dimension, conformal dimension, degree of multifractal non-uniformity, coefficient of multifractal asymmetry, index of lacunarity, and index of fractal anisotropy. The difference between morphological properties of mathematical and real-world fractals is especially outlined in this review paper. Full article
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