Two simple methods for overall determination of mobility in dynamic speckle patterns

Budini, Nicolás; Mulone, C.; Vincitorio, Fabio Miguel; Freyre, C.; Díaz, Ana Jesús López; Ramil, A.

doi:10.1016/j.ijleo.2013.05.119

Cited by 7 publications

(8 citation statements)

References 20 publications

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“…We have analyzed SA through a recently proposed method which is described in detail in Ref. [15]. Here we limit to show the basic equation to determine the SA from a sequence of images, which reads…”

Section: Methodology 21 Experimental Detailsmentioning

confidence: 99%

“…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%

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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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Section: Methodology 21 Experimental Detailsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic speckle study of microbial growth

et al. 2015

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“…Therefore, each SA value represents an average activity along an elapsed time Δτ ¼ ðN − 1Þτ. of this method are described elsewhere, 10 and here we limit to show its basic equation, which reads E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 1 ; 6 3 ; 7 3 0 SA ¼…”

Section: Appendix: Determination Of Sa From Speckle Imagesmentioning

confidence: 99%

“…Recently, we have also developed a simple algorithm to quantify globally the SA of dynamic speckle patterns, which is based on the calculation of the area fraction presenting variation between consecutive speckle images. 10 Despite the fact that SA quantification is really simple and straightforward, and also due to the complex relation between speckle patterns and the characteristics of the object under analysis, a clear understanding and a consistent explanation linking the observed dynamics with the underlying physical processes are still lacking. 11 Therefore, the combined implementation of dynamic speckle methods and other characterization techniques can bring some light into the mechanisms giving rise to the observed SA evolution of a particular object or sample under study.…”

Section: Introductionmentioning

confidence: 99%

Extraction of dynamic speckle activity information from digital holograms

et al. 2016

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In this work we show how dynamic speckle information can be extracted directly from digital holograms. This allows improving the analysis and characterization of dynamic phenomena by combining dynamic speckle with digital holographic interferometry measurements. We have studied the drying process of paint coatings, which is a typical study case in the field of dynamic speckle characterization, since the speckle activity (SA) of drying coatings is known to decay smoothly as a function of time. We recorded both holograms and speckle images during the process. In this way, we could compare the evolution of global SA calculated from speckle images by a standard method with the evolution of speckle correlation extracted directly from the holograms. The results obtained from both methods have shown to be in good agreement.

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“…Therefore, assessment of their quality and estimated shelf-life turns relevant, while, to our knowledge, there is no optical study performed by means of dynamic speckle methods on strawberries. Through the application of two recently developed algorithms for biospeckle analysis [15] we have inspected the correlation between the BA value and the aging or quality characteristics of the fruit, while maintained at room temperature conditions.…”

Section: Introductionmentioning

confidence: 99%

Biospeckle Activity Evolution of Strawberries

Mulone

Budini

Vincitorio

et al. 2014

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In this work, we measured the biospeckle activity of strawberries (fragaria ⇥ ananassa) with two recently developed algorithms. We observed an important diminution of speckle activity within time periods of 72 h. We tested the methods by analyzing different specimens to check for proper detection of bruised areas or fungal development. The obtained results serve as a starting point to correlate the time evolution of biospeckle activity with aging of fruits, in order to set the basis for development of future standardized fruit quality control procedures.

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Two simple methods for overall determination of mobility in dynamic speckle patterns

Cited by 7 publications

References 20 publications

Dynamic speckle study of microbial growth

Dynamic speckle study of microbial growth

Extraction of dynamic speckle activity information from digital holograms

Biospeckle Activity Evolution of Strawberries

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