Применение компьютерного зрения в сепарации семян зерновых культур = Computer vision in separation of cereal seeds / А. В. Власов, А. С. Фадеев

Set Level: Информационные технологии в науке, управлении, социальной сфере и медицине, сборник научных трудов III Международной научной конференции, 23-26 мая 2016 г., Томск, в 2 ч. = 2016Main Author: Власов, А. В., специалист в области информатики и вычислительной техники, аспирант Томского политехнического университета, 1991-, Андрей ВладимировичCoauthor: Фадеев, А. С., специалист в области информатики и вычислительной техники, проректор по цифровизации - директор центра цифровых образовательных технологий, доцент Томского политехнического университета, кандидат технических наук, 1981-, Александр СергеевичCorporate Author (Secondary): Национальный исследовательский Томский политехнический университет (ТПУ), Институт кибернетики (ИК), Кафедра автоматики и компьютерных систем (АИКС)Language: русский.Country: Россия.Series: Информационные системы и технологииAbstract: The most outstanding agricultural problem is a cereal seeds sorting. The sorting reduces the number of impurity seeds, causing the acceleration of growth and amount of the crop. These actions lead to economy prosperity. Today there are a lot of mechanical types of sorting, but they don't provide the required product yield. The paper is concerned with using of the computer vision technology as an additional sorting stage for a better accuracy. It provides a list of sorting criteria and some experimental results. A basic sorting method and some universalized intelligent approaches for unknown cultures are given. The possibility of corrupted or tinted seeds identification is described..Bibliography: [Библиогр.: с. 142 (5 назв.)].Subject: труды учёных ТПУ | электронные ресурсы | компьютерные технологии | компьютерное зрение | примеси | фотосепарация | гистограммы Online Resources:Click here to access online
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[Библиогр.: с. 142 (5 назв.)]

The most outstanding agricultural problem is a cereal seeds sorting. The sorting reduces the number of impurity seeds, causing the acceleration of growth and amount of the crop. These actions lead to economy prosperity. Today there are a lot of mechanical types of sorting, but they don't provide the required product yield. The paper is concerned with using of the computer vision technology as an additional sorting stage for a better accuracy. It provides a list of sorting criteria and some experimental results. A basic sorting method and some universalized intelligent approaches for unknown cultures are given. The possibility of corrupted or tinted seeds identification is described.

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