Multifractal characterisation and classification of bread crumb digital images

Autores
Baravalle, Rodrigo Guillermo; Delrieux, Claudio Augusto; Gómez, Juan Carlos
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Adequate models of the bread crumb structure can be critical for understanding flow and transport processes in bread manufacturing, creating synthetic bread crumb images for photo-realistic rendering, evaluating similarities, and establishing quality features of different bread crumb types. In this article, multifractal analysis, employing the multifractal spectrum (MFS), has been applied to study the structure of the bread crumb in four varieties of bread (baguette, sliced, bran, and sandwich). The computed spectrum can be used to discriminate among bread crumbs from different types. Also, high correlations were found between some of these parameters and the porosity, coarseness, and heterogeneity of the samples. These results demonstrate that the MFS is an appropriate tool for characterising the internal structure of the bread crumb, and thus, it may be used to establish important quality properties it should have. The MFS has shown to provide local and global image features that are both robust and low-dimensional, leading to feature vectors that capture essential information for classification tasks. Results show that the MFS-based classification is able to distinguish different bread crumbs with very high accuracy. Multifractal modelling of the underlying structure can be an appropriate method for parameterising and simulating the appearance of different bread crumbs.
Fil: Baravalle, Rodrigo Guillermo. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina
Fil: Gómez, Juan Carlos. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Materia
Fractal
Multifractal
Image Analysis
Image Classification
Feature Extraction
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/15160
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Multifractal characterisation and classification of bread crumb digital imagesBaravalle, Rodrigo GuillermoDelrieux, Claudio AugustoGómez, Juan CarlosFractalMultifractalImage AnalysisImage ClassificationFeature Extractionhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Adequate models of the bread crumb structure can be critical for understanding flow and transport processes in bread manufacturing, creating synthetic bread crumb images for photo-realistic rendering, evaluating similarities, and establishing quality features of different bread crumb types. In this article, multifractal analysis, employing the multifractal spectrum (MFS), has been applied to study the structure of the bread crumb in four varieties of bread (baguette, sliced, bran, and sandwich). The computed spectrum can be used to discriminate among bread crumbs from different types. Also, high correlations were found between some of these parameters and the porosity, coarseness, and heterogeneity of the samples. These results demonstrate that the MFS is an appropriate tool for characterising the internal structure of the bread crumb, and thus, it may be used to establish important quality properties it should have. The MFS has shown to provide local and global image features that are both robust and low-dimensional, leading to feature vectors that capture essential information for classification tasks. Results show that the MFS-based classification is able to distinguish different bread crumbs with very high accuracy. Multifractal modelling of the underlying structure can be an appropriate method for parameterising and simulating the appearance of different bread crumbs.Fil: Baravalle, Rodrigo Guillermo. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Gómez, Juan Carlos. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaSpringer2015-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/15160Baravalle, Rodrigo Guillermo; Delrieux, Claudio Augusto; Gómez, Juan Carlos; Multifractal characterisation and classification of bread crumb digital images; Springer; EURASIP Journal on Image and Video Processing; 2015; 9; 12-2015; 1-101687-5281enginfo:eu-repo/semantics/altIdentifier/url/http://jivp.eurasipjournals.com/content/2015/1/9info:eu-repo/semantics/altIdentifier/doi/10.1186/s13640-015-0063-8info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1186/s13640-015-0063-8info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:01:38Zoai:ri.conicet.gov.ar:11336/15160instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:01:39.215CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multifractal characterisation and classification of bread crumb digital images
title Multifractal characterisation and classification of bread crumb digital images
spellingShingle Multifractal characterisation and classification of bread crumb digital images
Baravalle, Rodrigo Guillermo
Fractal
Multifractal
Image Analysis
Image Classification
Feature Extraction
title_short Multifractal characterisation and classification of bread crumb digital images
title_full Multifractal characterisation and classification of bread crumb digital images
title_fullStr Multifractal characterisation and classification of bread crumb digital images
title_full_unstemmed Multifractal characterisation and classification of bread crumb digital images
title_sort Multifractal characterisation and classification of bread crumb digital images
dc.creator.none.fl_str_mv Baravalle, Rodrigo Guillermo
Delrieux, Claudio Augusto
Gómez, Juan Carlos
author Baravalle, Rodrigo Guillermo
author_facet Baravalle, Rodrigo Guillermo
Delrieux, Claudio Augusto
Gómez, Juan Carlos
author_role author
author2 Delrieux, Claudio Augusto
Gómez, Juan Carlos
author2_role author
author
dc.subject.none.fl_str_mv Fractal
Multifractal
Image Analysis
Image Classification
Feature Extraction
topic Fractal
Multifractal
Image Analysis
Image Classification
Feature Extraction
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Adequate models of the bread crumb structure can be critical for understanding flow and transport processes in bread manufacturing, creating synthetic bread crumb images for photo-realistic rendering, evaluating similarities, and establishing quality features of different bread crumb types. In this article, multifractal analysis, employing the multifractal spectrum (MFS), has been applied to study the structure of the bread crumb in four varieties of bread (baguette, sliced, bran, and sandwich). The computed spectrum can be used to discriminate among bread crumbs from different types. Also, high correlations were found between some of these parameters and the porosity, coarseness, and heterogeneity of the samples. These results demonstrate that the MFS is an appropriate tool for characterising the internal structure of the bread crumb, and thus, it may be used to establish important quality properties it should have. The MFS has shown to provide local and global image features that are both robust and low-dimensional, leading to feature vectors that capture essential information for classification tasks. Results show that the MFS-based classification is able to distinguish different bread crumbs with very high accuracy. Multifractal modelling of the underlying structure can be an appropriate method for parameterising and simulating the appearance of different bread crumbs.
Fil: Baravalle, Rodrigo Guillermo. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina
Fil: Gómez, Juan Carlos. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
description Adequate models of the bread crumb structure can be critical for understanding flow and transport processes in bread manufacturing, creating synthetic bread crumb images for photo-realistic rendering, evaluating similarities, and establishing quality features of different bread crumb types. In this article, multifractal analysis, employing the multifractal spectrum (MFS), has been applied to study the structure of the bread crumb in four varieties of bread (baguette, sliced, bran, and sandwich). The computed spectrum can be used to discriminate among bread crumbs from different types. Also, high correlations were found between some of these parameters and the porosity, coarseness, and heterogeneity of the samples. These results demonstrate that the MFS is an appropriate tool for characterising the internal structure of the bread crumb, and thus, it may be used to establish important quality properties it should have. The MFS has shown to provide local and global image features that are both robust and low-dimensional, leading to feature vectors that capture essential information for classification tasks. Results show that the MFS-based classification is able to distinguish different bread crumbs with very high accuracy. Multifractal modelling of the underlying structure can be an appropriate method for parameterising and simulating the appearance of different bread crumbs.
publishDate 2015
dc.date.none.fl_str_mv 2015-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/15160
Baravalle, Rodrigo Guillermo; Delrieux, Claudio Augusto; Gómez, Juan Carlos; Multifractal characterisation and classification of bread crumb digital images; Springer; EURASIP Journal on Image and Video Processing; 2015; 9; 12-2015; 1-10
1687-5281
url http://hdl.handle.net/11336/15160
identifier_str_mv Baravalle, Rodrigo Guillermo; Delrieux, Claudio Augusto; Gómez, Juan Carlos; Multifractal characterisation and classification of bread crumb digital images; Springer; EURASIP Journal on Image and Video Processing; 2015; 9; 12-2015; 1-10
1687-5281
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://jivp.eurasipjournals.com/content/2015/1/9
info:eu-repo/semantics/altIdentifier/doi/10.1186/s13640-015-0063-8
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1186/s13640-015-0063-8
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.993085

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