Computer vision-based image analysis for the estimation of acrylamide concentrations of potato chips and french fries

Abstract

In this study, digital colour images of fried potato chips and french fries were analyzed to estimate acrylamide levels based on the correlation with analyses using liquid chromatography-mass spectrometry. In fried potato images, bright yellow (Region 1), yellowish brown (Region 2) and darker brown (Region 3) regions were clearly visible, having different kinds of image pixels with characteristic mean values of red, green and blue components. Pixels of the fried potato image were classified into three sets (Set 1, Set 2 and Set 3) by means of semi-automatic and automatic segmentation. There was a strong correlation between acrylamide concentration and NA2 value, which is defined as the number of pixels in Set 2 divided by the total number of pixels of the entire fried potato image. To verify the applicability of this approach, a linear regression equation was used to estimate the acrylamide concentrations of a number of commercial potato chips and home-made french fries. Mean differences between the measured and predicted acrylamide concentrations were found to be +4 ± 14% and 14 ± 24% for commercial potato chips and home-made french fries, respectively