Physical Quality Investigation of Germinated Brown Rice by using Image Processing

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Sarawoot Boonkidram
Nattavut Sriwiboon


In this paper, we use the deep learning image processing technology and the CNN algorithm to investigate the quality of germinated brown rice. We compile the germinated brown rice digital images 500 samples of germinated brown rice and non-germinated brown rice, which classify by the experts and the folk philosopher. After that, we develop the program and use the images of the germinated brown rice 250 samples, and the images of non-germinated brown rice 250 samples to create a model for classifying quality the germinated brown rice. The results that are shown the use of CNN algorithms for creating a model demonstration the exceptional accuracy at 95.17%. Then, we develop the program to test the model that shown an accuracy of classifying the quality of germinated brown rice as high as 96%, including the classifying quality of non-germinated brown rice as accuracy of 84%.


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How to Cite
S. Boonkidram and N. Sriwiboon, “Physical Quality Investigation of Germinated Brown Rice by using Image Processing”, JIST, vol. 10, no. 2, pp. 101-109, Dec. 2020.
Research Article: Multidisciplinary (Detail in Scope of Journal)


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