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

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2014 Latin American Computing Conference, CLEI 2014
EditoresPablo Ezzatti, Andrea Delgado
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781479961306
DOI
EstadoPublicada - 21 nov. 2014
Evento2014 40th Latin American Computing Conference, CLEI 2014 - Montevideo, Uruguay
Duración: 15 set. 201419 set. 2014

Serie de la publicación

NombreProceedings of the 2014 Latin American Computing Conference, CLEI 2014

Conferencia

Conferencia2014 40th Latin American Computing Conference, CLEI 2014
País/TerritorioUruguay
CiudadMontevideo
Período15/09/1419/09/14

Nota bibliográfica

Publisher Copyright:
© 2014 IEEE.

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