Evaluation of laser dynamic speckle signals applying granular computing

Pra, Ana Lucía Dai; Passoni, Lucía Isabel; Rabal, H.

doi:10.1016/j.sigpro.2008.08.012

Cited by 20 publications

(17 citation statements)

References 25 publications

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“…The Rough-Fuzzy Granularity Descriptor, a computed within the time domain, is actually based in the Fuzzy Granular Descriptor (FGD) previously published, which quantifies the time intensity variations as fuzzy sets granules 10 . Next, the approach of Rough Set theory was introduced to define the intensity information granules and to adapt the algorithm to a real time implementation 11 .…”

Section: Rough-fuzzy Granularity Descriptor (Rfgd)mentioning

confidence: 99%

Signal Feature Extraction Using Granular Computing. Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns

Pra¹,

Passoni²,

Sendra³

et al. 2015

IJCIS

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The laser dynamic speckle is a phenomenon caused by the fluctuant interference of the laser light reflected from an illuminated surface where some kind of activity is taking place. Signals generated by the intensity changes in each pixel through the sequence are processed with the finality of identifying underlying activity in each point. In this work we compare the performance of a Rough Fuzzy Granular Descriptor (previously published) against a set of dynamic speckle descriptors based in time and frequency processing. To perform this evaluation a numerical simulation is proposed to explore their linearity, robustness, sensitivity related to the samples quantity, as well as also by their computing time. Also the robustness to inhomogeneous spatial intensity was evaluated in an experiment performed with the illuminated surface of an actual biological object.

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Section: Rough-fuzzy Granularity Descriptor (Rfgd)mentioning

confidence: 99%

Signal Feature Extraction Using Granular Computing. Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns

Pra¹,

Passoni²,

Sendra³

et al. 2015

IJCIS

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“…Among the tools that have been developed for these studies may include: correlation analysis, temporal analysis of cooccurrence matrix, wavelet analysis, granular, etc [10][11][12][13][14].…”

Section: Dynamic Specklementioning

confidence: 99%

Determination of coagulation time of human blood by biospeckle technique

et al. 2011

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When a lesion occurs in a blood vessel, a series of mechanisms are activated to stop hemorrhage by increasing blood viscosity at the wounded place.If a sample of blood extracted of the human body is illuminated with coherent light, a time varying speckle pattern is observed. It is show high activity at the start and decreases with time until it finally stop.The analysis of these patterns shows a degree of correlation between speckle activity and the temporal evolution of the clot.These preliminary results are promising for the continuation of studies aiming to the application of biospeckle techniques to the analysis of coagulation times.

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“…[45], where an account of the most recent techniques and processing algorithms for improving the quality of the DAM are described. The new developments include the construction of DAMs from wavelet entropy [39], the generation of DAMs of the NF speckle patterns from the spatial variance of the phase [46], by using the Empirical Decomposition Method [47], and by using granular computing [48]. As discussed in Ref.…”

Section: Novel Developments For Time and Space Resolved Scatteringmentioning

confidence: 99%

“…As discussed in Ref. [48] the selection of the methods for the analysis of dynamic speckle patterns is still empirical and relies of the effectiveness of the chosen procedure to solve a specific problem.…”

Section: Novel Developments For Time and Space Resolved Scatteringmentioning

confidence: 99%

Near-field scattering techniques: Novel instrumentation and results from time and spatially resolved investigations of soft matter systems

Cerbino

Vailati

2009

Current Opinion in Colloid & Interface Science

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Evaluation of laser dynamic speckle signals applying granular computing

Cited by 20 publications

References 25 publications

Signal Feature Extraction Using Granular Computing. Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns

Signal Feature Extraction Using Granular Computing. Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns

Determination of coagulation time of human blood by biospeckle technique

Near-field scattering techniques: Novel instrumentation and results from time and spatially resolved investigations of soft matter systems

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