Abstract
A study was conducted so as to develop a methodology for wheat variety discrimination and identification by way of image analysis techniques. The main purpose of this work was to determine a crucial set of parameters with respect to wheat grain morphology which best differentiate wheat varieties. To achieve better performance, the study was done by means of multivariate discriminant analysis. This utilized both forward and backward stepwise procedures based on various sets of geometric features. These parameters were extracted from the digitized X-ray images of wheat kernels obtained for three wheat varieties: Canadian, Kama, and Rosa. In our study, we revealed that selected combinations of geometric features permitted discriminant analysis to achieve a recognition rate of 89–96 %. We then compared the correctness of classification with results obtained by way of employing the nonparametric approach. The discriminant analysis proved effective in differentiating wheat varieties.
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- 1.
The maximum value of the compactness is equal to one and is taken for a circle.
- 2.
The ratio between the maximum diameter of the kernel in the vertical direction and the maximum diameter of the kernel in the horizontal direction, the measure of elongation.
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Charytanowicz, M., Niewczas, J., Kulczycki, P., Kowalski, P.A., Łukasik, S. (2016). Discrimination of Wheat Grain Varieties Using X-Ray Images. In: Piętka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technologies in Medicine. ITiB 2016. Advances in Intelligent Systems and Computing, vol 471. Springer, Cham. https://doi.org/10.1007/978-3-319-39796-2_4
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