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      • Department of Electrical and Electronics Engineering
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      Computer vision based analysis of potato chips-A tool for rapid detection of acrylamide level

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      Author(s)
      Gökmen, V.
      Senyuva, H. Z.
      Dülek, B.
      Çetin, E.
      Date
      2006
      Source Title
      Molecular Nutrition and Food Research
      Print ISSN
      1613-4125
      Electronic ISSN
      1613-4133
      Publisher
      Wiley - VCH Verlag GmbH & Co. KGaA
      Volume
      50
      Issue
      9
      Pages
      805 - 810
      Language
      English
      Type
      Article
      Item Usage Stats
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      258
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      Abstract
      In this study, analysis of digital color images of fried potato chips were combined with parallel LCMS based analysis of acrylamide in order to develop a rapid tool for the estimation of acrylamide during processing. Pixels of the fried potato image were classified into three sets based on their Euclidian distances to the representative mean values of typical bright yellow, yellowish brown, and dark brown regions using a semiautomatic segmentation algorithm. The featuring parameter extracted from the segmented image was NA2 value which was defined as the number of pixels in Set-2 divided by the total number of pixels of the entire fried potato image. Using training images of potato chips, it was shown that there was a strong linear correlation (r = 0.989) between acrylamide level and NA2 value. Images of a number of test samples were analyzed to predict their acrylamide level by means of this correlation data. The results confirmed that computer vision system described here provided explicit and meaningful description from the viewpoint of inspection and evaluation purpose for potato chips. Assuming a provisional threshold limit of 1000 ng/g for acrylamide, test samples could be successfully inspected with only one failure out of 60 potato chips.
      Keywords
      Acrylamide
      Computer vision
      Image analysis
      Potato chips
      Permalink
      http://hdl.handle.net/11693/23729
      Published Version (Please cite this version)
      https://doi.org/10.1002/mnfr.200500257
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      • Department of Electrical and Electronics Engineering 4011
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