• DocumentCode
    607914
  • Title

    Detection of high aflatoxin risk figs with computer vision

  • Author

    Gunes, Ahmet ; Durmus, E. ; Kalkan, H.

  • Author_Institution
    Bilgisayar Muhendisligi Bolumu, Suleyman Demirel Univ., Isparta, Turkey
  • fYear
    2013
  • fDate
    24-26 April 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Turkey produces major of the figs in world wide. Figs like other agricultural products (e.g hazelnuts, pistachio nuts, corn, etc.) may include cancerogenic aflatoxin. A majority of these aflatoxin contaminated figs may expose bright greenish-yellow fluorescence (BGYF) under UV illumination. These BGYF figs are manually detected and eliminated by workers in dark rooms. However, manual selection is tedious, subjective and the working condition threatens the worker´s healthy. In this study, a machine vision based non-destructive method is proposed for detecting the BGYF figs under UV illumination. Using the proposed methods, the BGYF and non-BGYF figs are classified with 0.93 area under curve value.
  • Keywords
    agricultural products; computer vision; contamination; food processing industry; food safety; production engineering computing; BGYF; Turkey; UV illumination; aflatoxin contaminated figs; agricultural products; bright greenish-yellow fluorescence; cancerogenic aflatoxin; computer vision; high aflatoxin risk figs; Chemistry; Computer vision; Computers; Fluorescence; Histograms; Lighting; Machine vision; Aflatoxin; computer vision; food safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2013 21st
  • Conference_Location
    Haspolat
  • Print_ISBN
    978-1-4673-5562-9
  • Electronic_ISBN
    978-1-4673-5561-2
  • Type

    conf

  • DOI
    10.1109/SIU.2013.6531575
  • Filename
    6531575