著者

神田 睦月 徳田 献一 入部 正継 森田 成昭 齊藤 安貴子 八上 修一 小堀 亮

出版者

一般社団法人 日本機械学会

雑誌

ロボティクス・メカトロニクス講演会講演概要集 2017 (ISSN:24243124)

巻号頁・発行日

pp.1A1-C02, 2017 (Released:2017-11-25)

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In recent years, aging of agricultural workers has progressed, attention is paid to ICT conversion of agriculture and Functional food with health maintenance effect. Raspberry contains a large amount of compounds that have a high health maintenance effect, which takes time and labor for cultivation. The purpose of this research is to construct an image processing system that recognizes color and position information in order to check whether harvesting of raspberries is possible under an indoor environment. As research contents, RGB values of colors of berries at various stages were calculated from spectral analysis results of berries and compared with actual fruit photos. We also classified colors in the image using machine learning and verified its accuracy.

著者

神田 睦月 徳田 献一 入部 正継 森田 成昭 齊藤 安貴子 八上 修一 小堀 亮

出版者

一般社団法人 日本機械学会

雑誌

ロボティクス・メカトロニクス講演会講演概要集

巻号頁・発行日

vol.2017, pp.1A1-C02, 2017

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<p>In recent years, aging of agricultural workers has progressed, attention is paid to ICT conversion of agriculture and Functional food with health maintenance effect. Raspberry contains a large amount of compounds that have a high health maintenance effect, which takes time and labor for cultivation. The purpose of this research is to construct an image processing system that recognizes color and position information in order to check whether harvesting of raspberries is possible under an indoor environment. As research contents, RGB values of colors of berries at various stages were calculated from spectral analysis results of berries and compared with actual fruit photos. We also classified colors in the image using machine learning and verified its accuracy.</p>