Влияние разработки инструментов и оптимальных методов очистки посевных культур семян с применением машинного зрения на развитие экономики аграрного сектора

Abstract

One of the major problems in agricultural production is the problem of procurement of cereal crops raw material, which should be pure and clean. Increasing the purity of raw materials allows to enhance yield, relevance and profitability of production. This article proposes a use of computer vision technologies as a photoseparation - an additional stage of more accurate cleaning of grain crop's seeds, which increases the purity of the harvest. The possibility of development and modification of the photoseparation method with the help of intelligent machine vision is described for the subsequent optimization of the technological process and expansion of the sorting properties.