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
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;
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
DOI :
10.1109/SIU.2013.6531575