Title :
Digital Image Processing for Classification of Coffee Cherries
Author :
Sandoval, Zulma ; Prieto, Flavio ; Betancur, Julián
Author_Institution :
Grupo de Investig. IET-UAC, Univ. Autonoma del Caribe, Barranquilla, Colombia
fDate :
Sept. 28 2010-Oct. 1 2010
Abstract :
A machine vision-based classification system to sort coffee fruits (cherries) according their ripeness stage is presented. Eight categories were defined and they include the entire coffee cherry ripeness process, from the initial stage (early green) to over-ripe and dry stages. A Bayesian classifier was implemented using a set of nine features which include color, shape and texture computed on an image of the fruit, with a 96.88% of performance using the cross-validation approach.
Keywords :
Bayes methods; agricultural engineering; computer vision; image classification; Bayesian classifier; coffee cherries; coffee fruits; digital image processing; machine vision-based classification system; Bayesian methods; Digital images; Feature extraction; Image color analysis; Manuals; Shape; Training;
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2010
Conference_Location :
Morelos
Print_ISBN :
978-1-4244-8149-1
DOI :
10.1109/CERMA.2010.54