Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.creator | Baravalle, Rodrigo Guillermo | - |
| dc.creator | Delrieux, Claudio Augusto | - |
| dc.creator | Gómez, Juan Carlos | - |
| dc.date | 2017-04-11T19:56:16Z | - |
| dc.date | 2017-04-11T19:56:16Z | - |
| dc.date | 2015-12 | - |
| dc.date | 2017-04-11T17:43:42Z | - |
| dc.date.accessioned | 2019-04-29T15:41:00Z | - |
| dc.date.available | 2019-04-29T15:41:00Z | - |
| dc.date.issued | 2017-04-11T19:56:16Z | - |
| dc.date.issued | 2017-04-11T19:56:16Z | - |
| dc.date.issued | 2015-12 | - |
| dc.date.issued | 2017-04-11T17:43:42Z | - |
| dc.identifier | 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 | - |
| dc.identifier | http://hdl.handle.net/11336/15160 | - |
| dc.identifier | 1687-5281 | - |
| dc.identifier.uri | http://rodna.bn.gov.ar:8080/jspui/handle/bnmm/299426 | - |
| dc.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. | - |
| dc.description | 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 | - |
| dc.description | 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 | - |
| dc.description | 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 | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.publisher | Springer | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/url/http://jivp.eurasipjournals.com/content/2015/1/9 | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1186/s13640-015-0063-8 | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1186/s13640-015-0063-8 | - |
| dc.rights | info:eu-repo/semantics/openAccess | - |
| dc.rights | https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | - |
| dc.source | reponame:CONICET Digital (CONICET) | - |
| dc.source | instname:Consejo Nacional de Investigaciones Científicas y Técnicas | - |
| dc.source | instacron:CONICET | - |
| dc.subject | Fractal | - |
| dc.subject | Multifractal | - |
| dc.subject | Image Analysis | - |
| dc.subject | Image Classification | - |
| dc.subject | Feature Extraction | - |
| dc.subject | Ciencias de la Computación | - |
| dc.subject | Ciencias de la Computación e Información | - |
| dc.subject | CIENCIAS NATURALES Y EXACTAS | - |
| dc.title | Multifractal characterisation and classification of bread crumb digital images | - |
| dc.type | info:eu-repo/semantics/article | - |
| dc.type | info:eu-repo/semantics/publishedVersion | - |
| dc.type | info:ar-repo/semantics/articulo | - |
| Aparece en las colecciones: | CONICET | |
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