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طراحی و پیاده سازی یک سامانه سمپاش دقیق برای مدیریت علف های هرز با استفاده از سیستم بینایی رایانه در مزرعه چغندرقند | ||
| تحقیقات سامانه‌ها و مکانیزاسیون کشاورزی | ||
| مقاله 9، دوره 20، شماره 72، تیر 1398، صفحه 123-142 اصل مقاله (1.17 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/erams.2018.114877.1211 | ||
| نویسندگان | ||
| هادی اورک1؛ سامان آبدانان مهدی زاده* 2 | ||
| 1دانشجوی کارشناسی ارشد دانشکده مهندسی زراعی و عمران روستایی، گروه مکانیک بیوسیستم، دانشگاه کشاورزی و منابع طبیعی رامین خوزستان | ||
| 2استادیار دانشکده مهندسی زراعی و عمران روستایی، گروه مکانیک بیوسیستم، دانشگاه کشاورزی و منابع طبیعی رامین خوزستان | ||
| چکیده | ||
| یکی از هدفهای کشاورزی دقیق به حداقل رساندن حجم علفکش با استفاده از سیستمهای مدیریتی علفهای هرز است. برای رسیدن به این هدف، سیستمی مبتنی بر پردازش تصویر بهمنظور تشخیص علفهای هرز در شرایط کنترل شده توسعه یافت. در این روش پیشنهادی از فضای رنگی HSV برای ایجاد تمایز بین پوشش گیاهیو پسزمینه و بین محصول مورد نظر و علفهای هرز استفاده گردید. در این پژوهش از کانال رنگی H از فضای رنگی HSV برای آستانهبندی خودکار و برخط پسزمینه (خاک) و پیشزمینه (علفهای هرز) استفاده شد که با اعمال فرسایش و اتساع مناسب، ناحیۀ مربوط به علفهای هرز و خاک شناسایی و آستانهبندی گردید. بر اساس نتایج بهدست آمده از آزمایش تشخیص علفهای هرز/چغندرقند، عملکرد (میزان تشخیص صحیح علفهای هرز) 94 درصد مشاهده شد. این سامانۀ هوشمند، در مقایسه با سمپاشهای معمولی (سمپاش Buferagri)، در آزمایش مزرعهای بهدلیل استفاده از فناوری بینایی کامپیوتر، مصرف محلول سم را 86/67 درصد کاهش داد. بنابراین استفاده از این روش به عنوان یک سامانه سمپاش هوشمند در مزارع چغندرقند پیشنهاد میشود. | ||
| کلیدواژه‌ها | ||
| پردازش تصویر؛ سمپاش هوشمند؛ تشخیص علف هرز | ||
| عنوان مقاله [English] | ||
| Design and Iimplementation of a Precision Sprayer System for Weed Management Using Computer Vision System (Case Study: Sugarbeet Farm) | ||
| نویسندگان [English] | ||
| Hadi Orak1؛ S. Abdanan-Mehdizade2 | ||
| 1MSc student of Mechanics of Biosystems Engineering Department, Faculty of Agricultural Engineering and Rural Development, Ramin Agriculture and Natural Resources University of Khuzestan. | ||
| 2Assistant Professor, Mechanics of Biosystems Engineering Department, Faculty of Agricultural Engineering and Rural Development, Ramin Agriculture and Natural Resources University of Khuzestan. | ||
| چکیده [English] | ||
| One of the objectives of precision agriculture is to minimize the volume of herbicide application by using weed management systems. To achieve this goal, a system based on image processing techniques was developed to detect weeds. In the proposed method, HSV color space was used to discriminate between vegetation and background, and between crops and weeds. In this research, the H component of HSV color space along with suitable erosion and dilation were used to automatically segment background (soil) and foreground (weed). According to what was obtained, the algorithm could identify weed from sugar beet plants with the accuracy of 94%. The intelligent sprayer system, in the field trials, in comparison with conventional sprayers (Buferagri sprayer), reduced 67.86% of volume of herbicide due to application of computer vision. The use of this method, as an intelligent sprayer system in sugar beet fields, is recommended. | ||
| کلیدواژه‌ها [English] | ||
| Computer Vision, Precision Sprayer, Sugar Beet, Weed Detection | ||
| مراجع | ||
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