• DocumentCode
    2173132
  • 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
  • fYear
    2010
  • fDate
    Sept. 28 2010-Oct. 1 2010
  • Firstpage
    417
  • Lastpage
    421
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2010
  • Conference_Location
    Morelos
  • Print_ISBN
    978-1-4244-8149-1
  • Type

    conf

  • DOI
    10.1109/CERMA.2010.54
  • Filename
    5692373