Title :
An approach for improve the recognition of defects in coffee beans using retinex algorithms
Author :
Guzman Apaza, Rel ; Portugal-Zambrano, Christian E. ; Gutierrez-Caceres, Juan C. ; Beltran-Castanon, Cesar A.
Author_Institution :
Catedra Concytec en Tecnol. de la informacion, Univ. Nac. de San Agustin, Arequipa, Peru
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.
Keywords :
feature extraction; food products; image colour analysis; image enhancement; image restoration; matrix algebra; object recognition; production engineering computing; support vector machines; CGLCM technique; MSRCR; SVM; coffee beans; coffee quality; color gray-level coocurrence matrix technique; defect recognition; digital images; feature extraction; image enhancement; multiscale retinex with color restoration; retinex algorithms; retinex theory; support vector machine; visual quality; Color; Electronic mail; Image color analysis; Irrigation; Manuals; Support vector machines; Visualization; CGLCM; Computer vision; MSRCR; SVM; coffee beans; image enhancement; industrial quality; retinex;
Conference_Titel :
Computing Conference (CLEI), 2014 XL Latin American
Conference_Location :
Montevideo
DOI :
10.1109/CLEI.2014.6965102