RT Book, Section
T1 Characterization of dynamic speckle sequences using principal component analysis and image descriptors
A1 López Alonso, José Manuel
A1 Grumel, Eduardo
A1 Cap, Nelly Lucía
A1 Trivi, Marcelo
A1 Rabal, Héctor
A1 Alda, Javier
AB Speckle is being used as a characterization tool for the analysis of the dynamic of slow varying phenomena occurring in biological and industrial samples. The retrieved data takes the form of a sequence of speckle images. The analysis of these images should reveal the inner dynamic of the biological or physical process taking place in the sample. Very recently, it has been shown that principal component analysis is able to split the original data set in a collection of classes. These classes can be related with the dynamic of the observed phenomena. At the same time, statistical descriptors of biospeckle images have been used to retrieve information on the characteristics of the sample. These statistical descriptors can be calculated in almost real time and provide a fast monitoring of the sample. On the other hand, principal component analysis requires longer computation time but the results contain more information related with spatial-temporal pattern that can be identified with physical process. This contribution merges both descriptions and uses principal component analysis as a pre-processing tool to obtain a collection of filtered images where a simpler statistical descriptor can be calculated. The method has been applied to slow-varying biological and industrial processes
PB SPIE
SN 978-162841764-7
YR 2015
FD 2015-09-09
LK https://hdl.handle.net/20.500.14352/24884
UL https://hdl.handle.net/20.500.14352/24884
LA eng
NO Copyright (2015) Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.9th Conference of Optics and Photonics for Information Processing; San Diego; United States; 10 August 2015 through 12 August 2015.ISSN: 0277786X
NO Ministerio de Economia y Competitividad of Spain
NO Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)  (Argentina)
NO Universidad Nacional de La Plata (UNLP) (Argentina)
DS Docta Complutense
RD 12 abr 2025