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

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 identi...

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Detalles Bibliográficos
Autores principales: Dai Pra, Ana Lucía, Passoni, Lucía Isabel, Sendra, G. Hernán, Trivi, Marcelo Ricardo, Rabal, Héctor Jorge
Formato: Articulo
Lenguaje:Inglés
Publicado: 2015
Materias:
Ingeniería
Biospeckle
dynamic speckle simulation
rough-fuzzy sets
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/86161
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-86161
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ingeniería
Biospeckle
dynamic speckle simulation
rough-fuzzy sets
spellingShingle Ingeniería
Biospeckle
dynamic speckle simulation
rough-fuzzy sets
Dai Pra, Ana Lucía
Passoni, Lucía Isabel
Sendra, G. Hernán
Trivi, Marcelo Ricardo
Rabal, Héctor Jorge
Signal Feature Extraction Using Granular Computing: Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns
topic_facet Ingeniería
Biospeckle
dynamic speckle simulation
rough-fuzzy sets
description 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.
format Articulo
Articulo
author Dai Pra, Ana Lucía
Passoni, Lucía Isabel
Sendra, G. Hernán
Trivi, Marcelo Ricardo
Rabal, Héctor Jorge
author_facet Dai Pra, Ana Lucía
Passoni, Lucía Isabel
Sendra, G. Hernán
Trivi, Marcelo Ricardo
Rabal, Héctor Jorge
author_sort Dai Pra, Ana Lucía
title Signal Feature Extraction Using Granular Computing: Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns
title_short Signal Feature Extraction Using Granular Computing: Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns
title_full Signal Feature Extraction Using Granular Computing: Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns
title_fullStr Signal Feature Extraction Using Granular Computing: Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns
title_full_unstemmed Signal Feature Extraction Using Granular Computing: Comparative Analysis with Frequency and Time Descriptors Applied to Dynamic Laser Speckle Patterns
title_sort signal feature extraction using granular computing: comparative analysis with frequency and time descriptors applied to dynamic laser speckle patterns
publishDate 2015
url http://sedici.unlp.edu.ar/handle/10915/86161
work_keys_str_mv AT daipraanalucia signalfeatureextractionusinggranularcomputingcomparativeanalysiswithfrequencyandtimedescriptorsappliedtodynamiclaserspecklepatterns
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AT sendraghernan signalfeatureextractionusinggranularcomputingcomparativeanalysiswithfrequencyandtimedescriptorsappliedtodynamiclaserspecklepatterns
AT trivimarceloricardo signalfeatureextractionusinggranularcomputingcomparativeanalysiswithfrequencyandtimedescriptorsappliedtodynamiclaserspecklepatterns
AT rabalhectorjorge signalfeatureextractionusinggranularcomputingcomparativeanalysiswithfrequencyandtimedescriptorsappliedtodynamiclaserspecklepatterns
bdutipo_str Repositorios
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