Discriminating defected and sound fruits of olive according to external damage area using image processing techniques

Journal Title: International Journal of Farming and Allied Sciences - Year 2014, Vol 3, Issue 6

Abstract

Olive is one of the fruits which are freshly consumed and its oil is used for cooking foods, producing drugs as well as industrial purposes. Nowadays, by increasing olive production, it is necessary to design and fabricate mechanized implements with high precision in sorting and grading processes in order to increase production output. To discriminate the defected and sound olives by image processing techniques, defect area was considered as a decisive factor in classification. A computer program, written in MATLAB 2011a, was used to process and analyze the images. By extracting the defected areas, two groups of olives (sound and defected) were classified in both LED and florescent illuminated samples. This task was done by classification analysis in toolbox of SPSS software. By conducting this analysis, the classification values obtained about 82.5 and 92.5% in florescent and LED illumination respectively.

Authors and Affiliations

Amir-Hossein Afkari-Sayyah, Hossein Azarmdel, Mansour Rasekh and Tarahom Mesri-Gundoshmian

Keywords

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  • EP ID EP32609
  • DOI -
  • Views 284
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How To Cite

Amir-Hossein Afkari-Sayyah, Hossein Azarmdel, Mansour Rasekh and Tarahom Mesri-Gundoshmian (2014). Discriminating defected and sound fruits of olive according to external damage area using image processing techniques. International Journal of Farming and Allied Sciences, 3(6), -. https://europub.co.uk./articles/-A-32609