IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v392y2013i7p1694-1701.html
   My bibliography  Save this article

Characterization of nanostructured material images using fractal descriptors

Author

Listed:
  • Florindo, João B.
  • Sikora, Mariana S.
  • Pereira, Ernesto C.
  • Bruno, Odemir M.

Abstract

This work presents a methodology to the morphology analysis and characterization of nanostructured material images acquired from FEG-SEM (Field Emission Gun-Scanning Electron Microscopy) technique. The metrics were extracted from the image texture (mathematical surface) by the volumetric fractal descriptors, a methodology based on the Bouligand–Minkowski fractal dimension, which considers the properties of the Minkowski dilation of the surface points. An experiment with galvanostatic anodic titanium oxide samples prepared in oxalyc acid solution using different conditions of applied current, oxalyc acid concentration and solution temperature was performed. The results demonstrate that the approach is capable of characterizing complex morphology characteristics such as those present in the anodic titanium oxide.

Suggested Citation

  • Florindo, João B. & Sikora, Mariana S. & Pereira, Ernesto C. & Bruno, Odemir M., 2013. "Characterization of nanostructured material images using fractal descriptors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1694-1701.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:7:p:1694-1701
    DOI: 10.1016/j.physa.2012.11.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437112009855
    Download Restriction: 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
    File URL: https://libkey.io/10.1016/j.physa.2012.11.020?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Tinghuai & Li, Lu & Ji, Sai & Wang, Xin & Tian, Yuan & Al-Dhelaan, Abdullah & Al-Rodhaan, Mznah, 2014. "Optimized Laplacian image sharpening algorithm based on graphic processing unit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 400-410.
    2. 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.
    3. Gonçalves, Wesley Nunes & Machado, Bruno Brandoli & Bruno, Odemir Martinez, 2014. "Texture descriptor combining fractal dimension and artificial crawlers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 358-370.
    4. Florindo, J.B. & Bruno, O.M., 2016. "Texture analysis by fractal descriptors over the wavelet domain using a best basis decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 415-427.

    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:phsmap:v:392:y:2013:i:7:p:1694-1701. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.