Time history speckle pattern under statistical view

Braga, Roberto A.; Silva, Washington Luis Santos; Sáfadi, Thelma; Nobre, C.M.B.

doi:10.1016/j.optcom.2007.12.069

Cited by 31 publications

(13 citation statements)

References 12 publications

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“…Additionally, more parameters is possible be investigated like motion history image (MHI), roughness parameters (skewness, kurtosis, etc.) without need to THSP 28,38,39 . The co-occurrence matrix (COM) can be considered as the intermediary matrix which is graphical is used for assessment of the consecutive pixels dispersion in a THSP of M points which monitors N samples.…”

Section: Numerical Processingmentioning

confidence: 99%

“…The surface characteristic affective definition of the sample under inspection is possible by analyzing dynamic speckle pattern in the characterization process field. Results of different analysis makes possible unfolding of the sample activity especially when samples include dynamic phenomenon makes more simple quantitative and qualitative knowledge in the sample under study 28,29 . The main purpose of the presented research is to determine the pitting corrosion activity through time.…”

Section: Numerical Processingmentioning

confidence: 99%

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Evaluation of pitting corrosion by dynamic speckle pattern analysis

Pedram

Jamali

Rad

et al. 2022

Preprint

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We use the dynamic speckle pattern method for the investigation of pitting corrosion. Pitting corrosion is a major failure mechanism in metals caused by the depassivation of a small area. The sample is Custom 450 stainless steel in 3.5 wt% NaCl solution and a potential of 350 mV SCE is applied to onset the corrosion. The analysis of the speckle patterns resulting from the laser scattering from the sample results in the quantitate evaluation of pitting during the experiment. The analysis shows that the growth rate of pitting in longer times decreases. This method for corrosion evaluation is low-cost, in situ, and easy to implement, and it is especially useful when the samples are difficult to reach for microscopic studies.

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Section: Numerical Processingmentioning

confidence: 99%

Section: Numerical Processingmentioning

confidence: 99%

Evaluation of pitting corrosion by dynamic speckle pattern analysis

Pedram

Jamali

Rad

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The THSP provides a graphical sign of the sample activity level that the higher the THSP line variation represents the higher activity of the sample under study 42 . The concept of the THSP is the foundation of numerical results exemplary co-occurrence matrix (COM), inertia moment (IM), and so on.…”

Section: Numerical Processingmentioning

confidence: 99%

Revealing the structure deformation in multi-component lipids by dynamic speckle pattern analysis

Panahi

Rad

Sasan

et al. 2021

Preprint

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In the bio-molecular field of Liquid-crystalline, the stacked lipid bilayers phase represents an extensive issue. It was proven that in addition to the typical smectic order, multi-component multilayer membranes could present columnar order arising from the coupling of two-dimensional intralayer phase separation. Interlayer smectic ordering distributes across hundreds of membrane lamellae, resulting in long-range alignment of phase-separated domains. In the current paper, the self-ordering of the sample over time is investigated by dynamic speckle pattern analysis. Temporal alteration of the sample is associated with changes in the intensity and contrast of the speckle pattern. We have used different factors, including motion history, co-occurrence, and time history speckle pattern, to examine the structure evolution of lipid mixtures, which are done by sequence images of speckle pattern over time. Roughness parameters inclusive of skewness and kurtosis of speckle pattern were investigated that are related to the domain size evolution of the sample. It is shown that the activity is decreasing by increasing the cholesterol content and inertia moment is inversely proportional with the growth of domain formation. The experimental setup, data recording, and data analysis are presented too.

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“…There are several approaches to quantify and analyze the SA of different specimens. Among them, one finds the analysis of speckle pattern's time history (THSP) by means of different descriptors like the inertia moment (IM) [4], the generalized differences (GD) method [8], the modified time correlation method [9], the time evolution inspection of the speckle pattern's texture [10], the contrast imaging method [11], the method of empirical mode decomposition [12], the Fujii difference method [13], the analysis of the speckle pattern's phase evolution [14], and so on. In a recent work we proposed a simple and straightforward algorithm [15] for calculating a single SA index from a sequence of images, aiming to simplify calculations and overcome some disadvantages of the mentioned methods.…”

Section: Introductionmentioning

confidence: 99%

Dynamic speckle study of microbial growth

et al. 2015

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In this work we present a characterization of yeast dynamic speckle activity during growth in an isolated agar culture medium. We found that it is possible to detect the growth of the microorganisms even before they turn out to be visible. By observing the time evolution of the speckle activity at different regions of the culture medium we could extract a map of the growth process, which served to analyze how the yeast develops and spreads over the agar's medium. An interesting point of this study concerns with the influence of the laser light on the yeast growth rate. We have found that yeast finds hard to develop at regions with higher laser light illumination, although we used a synchronous system to capture the speckle pattern. The results obtained in this work would serve us as a starting point to fabricate a detector of growing microorganism colonies, with obvious interesting applications in diverse areas.

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Time history speckle pattern under statistical view

Cited by 31 publications

References 12 publications

Evaluation of pitting corrosion by dynamic speckle pattern analysis

Evaluation of pitting corrosion by dynamic speckle pattern analysis

Revealing the structure deformation in multi-component lipids by dynamic speckle pattern analysis

Dynamic speckle study of microbial growth

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