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

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 2016 42nd Latin American Computing Conference, CLEI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509016334
DOIs
StatePublished - 25 Jan 2017
Event42nd Latin American Computing Conference, CLEI 2016 - Valparaiso, Chile
Duration: 10 Oct 201614 Oct 2016

Publication series

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

Conference

Conference42nd Latin American Computing Conference, CLEI 2016
Country/TerritoryChile
CityValparaiso
Period10/10/1614/10/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • coffee beans defects
  • Grade System
  • Histogram
  • Image Enhancement
  • Retinex
  • SVM
  • White Patch

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