Due to growing requirements concerning quality of products in food industry, it becomes important to introduce new, efficient, objective and repeatable automated methods of quality inspection. Agricultural products, such as cereal grains, are particularly difficult for automated inspection. This paper presents the results of experimental studies on the development of automated methods of manipulation and image acquisition of cereals, which can be used in machine vision systems for quality evaluation. Experimental studies were carried out on samples of brewing barley. The proof-of-concept evaluation of several methods was performed, on the basis of which the solution was chosen, based on the interaction of the screw and vibration feeders and bilateral image acquisition on moving transparent surface.
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