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http://dx.doi.org/10.5762/KAIS.2012.13.3.1319

Tomato sorting using independent component analysis on RGB images  

Ban, Jong-Oh (Dept. of Internet Business, Hallym Polytechnic University)
Kwon, Ki-Hyeon (Dept. of Information & Communication Engineering, Kangwon National University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.13, no.3, 2012 , pp. 1319-1324 More about this Journal
Abstract
Tomatoes were harvested at different ripening stages. To determine the ripening stages, We analyzed the relation between the compound concentrations of tomato measured with HPLC and the tomato RGB images. Among the compound concentrations, tomato quality is mostly affected by the Lycopene. The $Q^2$ error of the predicted Lycopene concentration and the corresponding independent component of tomato RGB image, determined from the PLS procedure, was 0.92. and we show the effectiveness of the independent component by comparing the error between the pixel area of RGB image applied by independent component and the simple black white tomato image. This regression made it possible to construct concentration images of the tomatoes, which showed non-uniform ripening. The method can be applied in an unsupervised real time sorting machine of unripe and discolored tomato using the compound concentrations.
Keywords
Independent Component Analysis; Tomato sorting; Concentration image;
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