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dc.creatorSchneider, Bruno de Oliveira-
dc.creatorAlves, Marcelo de Carvalho-
dc.date.accessioned2020-09-03T18:06:38Z-
dc.date.available2020-09-03T18:06:38Z-
dc.date.issued2020-
dc.identifier.citationSCHNEIDER, B. de O.; ALVES, M. de C. Digital image processing and spectral data source in seed analysis. CAB Reviews, Wallingford, n. 40, p. 1-6, 2020. DOI: 10.1079/PAVSNNR202015040.pt_BR
dc.identifier.urihttps://www.cabdirect.org/cabdirect/abstract/20203280833pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/42840-
dc.description.abstractImage processing is currently gaining lots of attention at seed quality labs as well as grain quality labs for being nondestructive, faster, and more objective than traditional seed or grain analysis methods. While seed analysts focus on quality parameters that will ensure vigorous plants, grain analysts focus on parameters related to safety or grading of the grain using roughly the same methods. We observed that few techniques on image processing have been used and that image data source roughly shapes research work done. The main data sources are visible light, hyperspectral imaging in the infrared section, and X-ray. Laser speckle is not so common but was also included. We have also noted that ultrasound imaging and magnetic resonance are also used for analysis, but these data sources were left out because of little work found.pt_BR
dc.languageenpt_BR
dc.publisherCABIpt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceCAB Reviewspt_BR
dc.subjectImage analysispt_BR
dc.subjectImage processingpt_BR
dc.subjectSeedspt_BR
dc.subjectSeed qualitypt_BR
dc.subjectGrainpt_BR
dc.subjectProcessamento digital de imagenspt_BR
dc.subjectAnálise de imagempt_BR
dc.subjectSementes - Análisept_BR
dc.subjectSementes - Qualidadept_BR
dc.subjectGrãospt_BR
dc.titleDigital image processing and spectral data source in seed analysispt_BR
dc.typeArtigopt_BR
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DEG - Artigos publicados em periódicos

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