Mostrar el registro sencillo del ítem
dc.contributor.author
Larese, Monica Graciela
dc.contributor.author
Granitto, Pablo Miguel
dc.date.available
2018-07-19T17:34:51Z
dc.date.issued
2016-07
dc.identifier.citation
Larese, Monica Graciela; Granitto, Pablo Miguel; Finding local leaf vein patterns for legume characterization and classification; Springer; Machine Vision And Applications; 27; 5; 7-2016; 709-720
dc.identifier.issn
0932-8092
dc.identifier.uri
http://hdl.handle.net/11336/52646
dc.description.abstract
In recent years, the importance of analyzing the effect of genetic variations on the plant phenotypes has raised much attention. In this paper, we describe a procedure which can be useful to discover representative leaf vein patterns for each species or variety under analysis. We consider three legumes, namely red bean, white bean and soybean. Soybean specimens are also divided in three cultivars. In total there are five leaf vein image classes. In order to find the discriminative patterns, we detect Self-Invariant Feature Transform (SIFT) keypoints in the segmented vein images. The Bag of Words model is built using SIFT descriptors, and classification is performed resorting to Support Vector Machines with a Gaussian kernel. Classification accuracies outperform recent results available in the literature and manual classification, showing the advantages of the procedure. The Bag of Words model is useful for vein patterns characterization and provides a means to highlight the most representative patterns for each species and variety.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Leaf Vein Characterization
dc.subject
Legume Species And Varieties Classification
dc.subject
Plant Phenotyping
dc.subject.classification
Ciencias de la Computación
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Finding local leaf vein patterns for legume characterization and classification
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-07-18T20:41:02Z
dc.journal.volume
27
dc.journal.number
5
dc.journal.pagination
709-720
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Nueva York
dc.description.fil
Fil: Larese, Monica Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
dc.description.fil
Fil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
dc.journal.title
Machine Vision And Applications
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1007/s00138-015-0732-8
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs00138-015-0732-8
Archivos asociados