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    A simplified and powerful image processing methods to separate Thai jasmine rice and sticky rice varieties
    (2018-01-01)
    Khondok, Piyoros
    ;
    Sakulkalavek, Aparporn
    ;
    Suwansukho, Kajpanya
    A simplified and powerful image processing procedures to separate the paddy of KHAW DOK MALI 105 or Thai jasmine rice and the paddy of sticky rice RD6 varieties were proposed. The procedures consist of image thresholding, image chain coding and curve fitting using polynomial function. From the fitting, three parameters of each variety, perimeters, area, and eccentricity, were calculated. Finally, the overall parameters were determined by using principal component analysis. The result shown that these procedures can be significantly separate both varieties.
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    Single-wavelength based thai jasmine rice identification with polynomial fitting function and neural network analysis
    (2013-09-18)
    Suwansukho, Kajpanya
    ;
    Sumriddetchkajorn, Sarun
    ;
    Buranasiri, Prathan
    We previously showed that a combination of image thresholding, chain coding, elliptic Fourier descriptors, and artificial neural network analysis provided a low false acceptance rate (FAR) and a false rejection rate (FRR) of 11.0% and 19.0%, respectively, in identify Thai jasmine rice from three unwanted rice varieties. In this work, we highlight that only a polynomial function fitting on the determined chain code and the neural network analysis are highly sufficient in obtaining a very low FAR of < 3.0% and a very low 0.3% FRR for the separation of Thai jasmine rice from Chainat 1 (CNT1), Prathumtani 1 (PTT1), and Hom-Pitsanulok (HPSL) rice varieties. With this proposed approach, the analytical time is tremendously suppressed from 4,250 seconds down to 2 seconds, implying extremely high potential in practical deployment. © 2013 SPIE.