Multiscale Fractal Descriptors Applied to Nanoscale Images

Florindo, João Batista; Sikora, Mariana S.; Pereira, Ernesto C.; Bruno, Odemir Martinez

doi:10.1007/s10948-012-1449-9

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…In order to make quantitative estimation of complexity of the obtained structures, the fractional metric Hausdorff-Besicovitch dimension (Feder 1988) was used. It was supposed that the formed structures displayed properties of affine self-similarity in a certain range of scale.…”

Section: Resultsmentioning

confidence: 99%

“…Such behavior is typical for all fractals. It is well known that the analysis of affine self-similar statistical fractals is used for the study and classification of various surfaces containing random inhomogeneities (Florindo 2012;Krasteva 2013;Raoufi 2001;Yadav 2012). The fractional metric dimension of Hausdorff-Besicovitch was obtained with the use of Fractal Analysis System for Windows Ver.3.4.7 software (Sasaki 1994) from SEM images edited by means of the procedure described below.…”

Section: Resultsmentioning

confidence: 99%

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Experimental study of fractal clusters formation from nanoparticles synthesized by atmospheric pressure plasma-enhanced chemical vapor deposition

2014

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This paper presents the experimental results from the fractal structures formation from nanoparticles of silicone dioxide deposited on the silicon substrate surface. Nanoparticles are synthesized by atmospheric pressure plasma-enhanced chemical vapor deposition with the use of capacitively coupled radio frequency (13.56 MHz) discharge sustained in helium atmosphere. Tetraethoxysilane is chosen as the test precursor. Correlation between the morphology of obtained deposits and the process parameters is found. The capability of nanoparticles movement along the deposit surface in local near-surface electric field is demonstrated. The empirical model that satisfactorily explained the mechanism of fractal clusters formation from nanoparticles on the substrate surface is developed. The model indicates that the dynamics of deposit morphology variations is determined by two competing processes: electrical charge transfer by nanoparticles to the deposit surface and electrical charge running off over the surface under conditions of changeable conductivity of the deposit surface.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Experimental study of fractal clusters formation from nanoparticles synthesized by atmospheric pressure plasma-enhanced chemical vapor deposition

2014

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“…Other approaches of extracting particle features from images involve additional mathematical transformations, with examples being wavelet (Kockentiedt & Toennies, ) and Fourier descriptors (Rice et al ., ; Fernandez Martinez et al ., ) or the Minkowski functionals and valuations, where particles are interpreted as graphs, with faces, edges, and vertices (Zhang et al ., ). The application of fractal dimensions (Florindo et al ., , ; Florindo & Bruno, ) is another type of approach to analysing particles. It is also possible to calculate lacunarity (Allain & Cloitre, ) – size distribution of the holes in the fractal.…”

Section: Introductionmentioning

confidence: 97%

Scanning electron microscopy image representativeness: morphological data on nanoparticles

Odziomek

Ushizima

Oberbek

et al. 2016

Journal of Microscopy

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A sample of a nanomaterial contains a distribution of nanoparticles of various shapes and/or sizes. A scanning electron microscopy image of such a sample often captures only a fragment of the morphological variety present in the sample. In order to quantitatively analyse the sample using scanning electron microscope digital images, and, in particular, to derive numerical representations of the sample morphology, image content has to be assessed. In this work, we present a framework for extracting morphological information contained in scanning electron microscopy images using computer vision algorithms, and for converting them into numerical particle descriptors. We explore the concept of image representativeness and provide a set of protocols for selecting optimal scanning electron microscopy images as well as determining the smallest representative image set for each of the morphological features. We demonstrate the practical aspects of our methodology by investigating tricalcium phosphate, Ca (PO ) , and calcium hydroxyphosphate, Ca (PO ) (OH), both naturally occurring minerals with a wide range of biomedical applications.

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“…Thus, these descriptors are capable of providing very rich information about the morphology of the material and, consequently, are a strong method for nanostructured material characterization task. The use of the Volumetric Fractal Descriptors applied to nano structured surfaces was initially proposed in [9]. In that seminal project, was suggested that Fractal Volumetric Descriptors could be used to characterize and analyze such nanostructures, showing the discrimination power on two distinct conditions.…”

Section: Introductionmentioning

confidence: 99%

Characterization of nanostructured material images using fractal descriptors

Florindo

Sikora

Pereira

et al. 2013

Physica A: Statistical Mechanics and its Applications

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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.

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Multiscale Fractal Descriptors Applied to Nanoscale Images

Cited by 5 publications

References 20 publications

Experimental study of fractal clusters formation from nanoparticles synthesized by atmospheric pressure plasma-enhanced chemical vapor deposition

Experimental study of fractal clusters formation from nanoparticles synthesized by atmospheric pressure plasma-enhanced chemical vapor deposition

Scanning electron microscopy image representativeness: morphological data on nanoparticles

Characterization of nanostructured material images using fractal descriptors

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