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Memorias de investigación
Artículos en revistas:
Application of independent components analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration
Año:2016
Áreas de investigación
  • Agricultura,
  • Ingenierías
Datos
Descripción
In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained.
Internacional
Si
JCR del ISI
Si
Título de la revista
Journal of Food Engineering
ISSN
0260-8774
Factor de impacto JCR
2,576
Información de impacto
Datos JCR del año 2013
Volumen
168
DOI
http://dx.doi.org/10.1016/j.jfoodeng.2015.07.008
Número de revista
Desde la página
7
Hasta la página
15
Mes
SIN MES
Ranking
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Participantes
  • Autor: Puneet Mishra . (UPM)
  • Autor: Christophe B.Y. Cordella (Inra UMR1145 GENIAL, Analytical Chemistry Laboratory, Francia)
  • Autor: Douglas Rutledge (AgroParisTech UMR1145 GENIAL, Analytical Chemistry Laboratory, Francia)
  • Autor: Jean Michel Roger (Irstea, Francia)
  • Autor: Pilar Barreiro Elorza (UPM)
  • Autor: Belen Diezma Iglesias (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: LPF-TAGRALIA: Técnicas Avanzadas en Agroalimentación
  • Departamento: Ingeniería Agroforestal
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