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A combined method of diagnosing the surface of grain using multispectral imaging technology in polarized light for automatic evaluation of grain quality has been analyzed. Polarized light in our experiment increases the spectral effect. We propose parameters for quantitative characterization of damages of the samples under the streaming data automation process on the base of the NI Vision platform with special narrow band-pass filters of Asahi Spectra Co. Ltd, Japan. A receiving of streaming data about the damages of grains can be fully automated on the base of the platform of NI Vision.

Automatic Controls of Food Quality Using the NI Vision System and Multispectral Images Technologies