An approach for improve the recognition of defects in coffee beans using retinex algorithms

Rel Guzmán Apaza, Christian E. Portugal-Zambrano, Juan Carlos Gutierrez Caceres, César A. Beltrán-Castañón

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

5 Scopus citations

Abstract

This paper describes the development of a system for evaluating the quality of coffee focused on the pre-processing of digital images using an algorithm based on the retinex theory called multi-scale retinex with color restoration (MSRCR). A dataset of images of coffee beans are collected and others techniques for image enhancement are compared, then a color gray-level coocurrence matrix (CGLCM) technique is used for features extraction and a Support Vector Machine (SVM) is used to evaluate results with a set of prepared data, these results shows a good visual quality and better accuracy in classification for MSRCR techniques compared with others, finally conclusions and future works are presented.

Original languageEnglish
Title of host publicationProceedings of the 2014 Latin American Computing Conference, CLEI 2014
EditorsPablo Ezzatti, Andrea Delgado
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479961306
DOIs
StatePublished - 21 Nov 2014
Event2014 40th Latin American Computing Conference, CLEI 2014 - Montevideo, Uruguay
Duration: 15 Sep 201419 Sep 2014

Publication series

NameProceedings of the 2014 Latin American Computing Conference, CLEI 2014

Conference

Conference2014 40th Latin American Computing Conference, CLEI 2014
Country/TerritoryUruguay
CityMontevideo
Period15/09/1419/09/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • CGLCM
  • coffee beans
  • Computer vision
  • image enhancement
  • industrial quality
  • MSRCR
  • retinex
  • SVM

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