Computer vision grading system for physical quality evaluation of green coffee beans

Christian E. Portugal-Zambrano, Juan C. Gutierrez-Caceres, Juan Ramirez-Ticona, Cesar A. Beltran-Castanon

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

7 Citas (Scopus)

Resumen

Evaluating the physical defects of green coffee beans are an important process in defining their quality. This evaluation is normally carried out by visual inspection or using traditional instruments which have some limitations. This work is focused on the implementation of a computer vision system combining a hardware prototype and a software module. The hardware was developed to capture the images of coffee beans, the software uses a White-Patch algorithm as a image enhancement procedure, color histograms as feature extractor and SVM for the classification task, a database of 1930 images was collected, we used 13 categories of defects described in the SCAA standard of evaluation. Results of classification achieved a 98.8% of overall detection accuracy, therefore the proposed system proved to be effective in classifying physical defects of green coffee beans. Finally a set of conclusions and future works are presented.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2016 42nd Latin American Computing Conference, CLEI 2016
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781509016334
DOI
EstadoPublicada - 25 ene. 2017
Evento42nd Latin American Computing Conference, CLEI 2016 - Valparaiso, Chile
Duración: 10 oct. 201614 oct. 2016

Serie de la publicación

NombreProceedings of the 2016 42nd Latin American Computing Conference, CLEI 2016

Conferencia

Conferencia42nd Latin American Computing Conference, CLEI 2016
País/TerritorioChile
CiudadValparaiso
Período10/10/1614/10/16

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