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dc.contributor.authorCRUVINEL, P. E.
dc.contributor.authorMINATEL, E. R.
dc.date.accessioned2025-04-09T14:47:54Z-
dc.date.available2025-04-09T14:47:54Z-
dc.date.created2003-08-19
dc.date.issued2002
dc.identifier.citationIn: WORLD CONGRESS OF COMPUTERS IN AGRICULTURE AND NATURAL RESOURCES-WCCA, 2002, Iguaçu Falls. 7 f. Disponível em <http://wcca.ifas.ufl.edu/technicalprogram1.html > Acessado em: 11.11.2002.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/24743-
dc.descriptionA rapid method for automated classification of oranges in living trees by size has been developed. It is based on image processing with correlation analysis in the frequency domain. This technique has the advantage of being a direct measurement method that automatically idenfies and counts oranges for quality control. Calibration was performed using standard imae with known orange sizes. Orange's sizes, ranging from less then 2 cm to over 10 cm in diameter have been automatically recognized and successfully measured. Error was not larger than 1.4%. In addition, practical examples of use of the method for determining characteristics of oranges are presented.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectMachine vision
dc.subjectAgricultural instrumentation
dc.subjectOrange measurement
dc.titleImage processing in automated pattern classification of oranges.
dc.typeArtigo em anais e proceedings
riaa.ainfo.id24743
riaa.ainfo.lastupdate2025-04-09
dc.contributor.institutionEmbrapa Instrumentação Agropecuária, São Carlos, SP.
Aparece en las colecciones:Artigo em anais de congresso (CNPDIA)

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