Artículo
Dynamic speckle image segmentation using Self-Organizing Maps
Dai Pra, Ana Lucia; Meschino, Gustavo Javier; Guzmán, Marcelo Nicolás
; Scandurra, Adriana Gabriela; González, Anabel Mariela; Weber, Christian
; Trivi, Marcelo Ricardo; Rabal, Hector Jorge
; Passoni, Lucía Isabel
Fecha de publicación:
07/2016
Editorial:
IOP Publishing
Revista:
Journal of Optics (United Kingdom)
ISSN:
1464-4258
e-ISSN:
2040-8986
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The aim of this work is to build a computational model able to automatically identify, after training, dynamic speckle pattern regions with similar properties. The process is carried out using a set of descriptors applied to the intensity variations with time in every pixel of a speckle image sequence. An image obtained by projecting a self-organized map is converted into regions of similar activity that can be easily distinguished. We propose a general procedure that could be applied to numerous situations. As examples we show different situations: (a) an activity test in a simplified situation; (b) a non-biological example and (c) biological active specimens. The results obtained are encouraging; they significantly improve upon those obtained using a single descriptor and will eventually permit automatic quantitative assessment.
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Articulos(CCT - MAR DEL PLATA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - MAR DEL PLATA
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - MAR DEL PLATA
Articulos(CIOP)
Articulos de CENTRO DE INVEST.OPTICAS (I)
Articulos de CENTRO DE INVEST.OPTICAS (I)
Citación
Dai Pra, Ana Lucia; Meschino, Gustavo Javier; Guzmán, Marcelo Nicolás; Scandurra, Adriana Gabriela; González, Anabel Mariela; et al.; Dynamic speckle image segmentation using Self-Organizing Maps; IOP Publishing; Journal of Optics (United Kingdom); 18; 8; 7-2016; 1-12
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