IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v156y2022ics0960077922000224.html
   My bibliography  Save this article

Dependence of multifractal analysis parameters on the darkness of a processed image

Author

Listed:
  • Martsepp, Merike
  • Laas, Tõnu
  • Laas, Katrin
  • Priimets, Jaanis
  • Tõkke, Siim
  • Mikli, Valdek

Abstract

In this study, four specimens of pure tungsten, which have been irradiated with a high-temperature plasma with 20, 40, 60, and 80 pulses, respectively, are considered. Scanning electron microscopy (SEM) and optical microscope (OM) images of these specimens are used to search for more suitable degrees of darkness for binarizing the images for multifractal analysis. The multifractal characteristics obtained from SEM and OM images are then compared for the same specimens. The study shows the application of multifractal analysis to SEM images is robust enough as the change of binarization level in a range of 30-70% leads to a change of multifractal characteristics about 0.5%. It has been found that the optimal binarization level for OM images is about 10%.

Suggested Citation

  • Martsepp, Merike & Laas, Tõnu & Laas, Katrin & Priimets, Jaanis & Tõkke, Siim & Mikli, Valdek, 2022. "Dependence of multifractal analysis parameters on the darkness of a processed image," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:chsofr:v:156:y:2022:i:c:s0960077922000224
    DOI: 10.1016/j.chaos.2022.111811
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077922000224
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2022.111811?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sijilmassi, Ouafa & López Alonso, José-Manuel & Del Río Sevilla, Aurora & Barrio Asensio, María del Carmen, 2020. "Multifractal analysis of embryonic eye structures from female mice with dietary folic acid deficiency. Part I: Fractal dimension, lacunarity, divergence, and multifractal spectrum," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Gabriel-Guzmán, Mauricio & Rivera, Victor M. & Cocotle-Ronzón, Yolanda & García-Díaz, Samuel & Hernandez-Martinez, Eliseo, 2017. "Fractality in coffee bean surface for roasting process," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 79-84.
    3. Panigrahy, Chinmaya & Seal, Ayan & Mahato, Nihar Kumar & Bhattacharjee, Debotosh, 2019. "Differential box counting methods for estimating fractal dimension of gray-scale images: A survey," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 178-202.
    4. Chauveau, Julien & Rousseau, David & Richard, Paul & Chapeau-Blondeau, François, 2010. "Multifractal analysis of three-dimensional histogram from color images," Chaos, Solitons & Fractals, Elsevier, vol. 43(1), pages 57-67.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huzak, Renato & Vlah, Domagoj & Žubrinić, Darko & Županović, Vesna, 2023. "Fractal analysis of degenerate spiral trajectories of a class of ordinary differential equations," Applied Mathematics and Computation, Elsevier, vol. 438(C).
    2. Zuo, Xue & Tang, Xiang & Zhou, Yuankai, 2020. "Influence of sampling length on estimated fractal dimension of surface profile," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    3. Eugenio Ivorra & Juan Camilo Sarria-González & Joel Girón-Hernández, 2020. "Computer vision techniques for modelling the roasting process of coffee (Coffea arabica L.) var. Castillo," Czech Journal of Food Sciences, Czech Academy of Agricultural Sciences, vol. 38(6), pages 388-396.
    4. Bruno Rafael de Almeida Moreira & Ronaldo da Silva Viana & Victor Hugo Cruz & Paulo Renato Matos Lopes & Celso Tadao Miasaki & Anderson Chagas Magalhães & Paulo Alexandre Monteiro de Figueiredo & Luca, 2020. "Anti-Thermal Shock Binding of Liquid-State Food Waste to Non-Wood Pellets," Energies, MDPI, vol. 13(12), pages 1-26, June.
    5. Lahmiri, Salim, 2016. "Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 235-243.
    6. Jiang, Kai & Liu, Zhifeng & Tian, Yang & Zhang, Tao & Yang, Congbin, 2022. "An estimation method of fractal parameters on rough surfaces based on the exact spectral moment using artificial neural network," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    7. Chéné, Yann & Belin, Étienne & Rousseau, David & Chapeau-Blondeau, François, 2013. "Multiscale analysis of depth images from natural scenes: Scaling in the depth of the woods," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 135-149.
    8. Zenteno-Catemaxca, Rolando & Moguel-Castañeda, Jazael G. & Rivera, Victor M. & Puebla, Hector & Hernandez-Martinez, Eliseo, 2021. "Monitoring a chemical reaction using pH measurements: An approach based on multiscale fractal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    9. Jia, Li & Peng, Shoujian & Wu, Bin & Xu, Jiang & Yan, Fazhi & Chen, Yuexia, 2023. "Exploration on the characteristics of 3D crack network expansion induced by hydraulic fracturing: A hybrid approach combining experiments and algorithms," Energy, Elsevier, vol. 282(C).
    10. Zeng, Ziyue & Xiao, Fuyuan, 2023. "A new complex belief entropy of χ2 divergence with its application in cardiac interbeat interval time series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    11. Ramírez-Platas, Mariana & Morales-Cabrera, Miguel A. & Rivera, Victor M. & Morales-Zarate, Epifanio & Hernandez-Martinez, Eliseo, 2021. "Fractal and multifractal analysis of electrochemical noise to corrosion evaluation in A36 steel and AISI 304 stainless steel exposed to MEA-CO2 aqueous solutions," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:156:y:2022:i:c:s0960077922000224. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.