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توسعه سامانه هوشمند تشخیص بیماری آتشک در گیاه لیلیوم با استفاده از روش پردازش تصویر | ||
مهندسی بیوسیستم ایران | ||
مقاله 4، دوره 50، شماره 3، آبان 1398، صفحه 535-546 اصل مقاله (1.21 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijbse.2019.268871.665112 | ||
نویسندگان | ||
حدیث بی آبی1؛ سامان آبدانان مهدی زاده* 2؛ محمدرضا صالحی سلمی3 | ||
1دانشجوی کارشناسی ارشد، دانشکده مهندسی زراعی و عمران روستایی، گروه مکانیک بیوسیستم، دانشگاه علوم کشاورزی و منابع طبیعی خوزستان | ||
2استادیار گروه مهندسی مکانیک بیوسیستم، دانشکده مهندسی زراعی و عمران روستایی، دانشگاه علوم کشاورزی و منابع طبیعی خوزستان، اهواز، ایران | ||
3استادیار دانشکدة کشاورزی، گروه علوم باغبانی، دانشگاه کشاورزی و منابع طبیعی رامین خوزستان | ||
چکیده | ||
تشخیص خودکار بیماریهای گیاهی در مراحل اولیه در مزارع بزرگ میتواند علاوه بر افزایش کیفیت محصول نهایی از بروز خسارات جبران ناپذیر نیز جلوگیری نماید. لذا در این پژوهش سامانهای هوشمند بر مبنای پردازش تصاویر به منظور شناسایی و رفع بیماری آتشک در برگ گیاه لیلیوم و همچنین طبقهبندی گیاه سالم از بیمار طراحی و توسعه یافت. بر این اساس تعداد 20 گل سالم و 20 گل آلوده توسط سامانه بینایی ماشین ارزیابی شدند. به منظور طبقهبندی گیاهان تعداد 19 ویژگی رنگی و موفولوژیگی از گیاه استخراج و موثرترین این ویژگیها (L برگ، a برگ، b برگ، L ساقه و طول ساقه) با کمک روش آنتروپی فازی انتخاب و به وسیله طبقهبند مشابه گروهبندی گردیدند. راندمان الگوریتم پیشنهادی در تشخیص و طبقهبندی بیماری برای آنتروپی فازی H1، آنتروپی فازی H2/H3 و بدون انتخاب ویژگی به ترتیب 15/96، 18/93 و 3/84 بدست آمد. | ||
کلیدواژهها | ||
بیماری برگ گیاه؛ پردازش تصویر؛ آنتروپی فازی و طبقهبند مشابه | ||
عنوان مقاله [English] | ||
Development of an Intelligent System for Diagnosis of the Botrytis Elliptica Disease in the Lilium Plant Using Image Processing | ||
نویسندگان [English] | ||
Hadis Biabi1؛ Saman Abdanan Mehdizadeh2؛ Mohamadreza Salehi Salmi3 | ||
1Department of Mechanics of Biosystems Engineering, Faculty of Agricultural and Rural Development, Agricultural Sciences and Resources University of Khuzestan, Ahvaz, Khuzestan Iran | ||
2Assistant professor, Department of Mechanics of Biosystems Engineering, Faculty of Agricultural and Rural Development, Agricultural Sciences and Resources University of Khuzestan, Ahvaz, Khuzestan Iran | ||
3Assistant professor, Horticultural Science Department, Faculty of Agriculture, Agricultural Sciences and Resources University of Khuzestan | ||
چکیده [English] | ||
The automatic detection of plant diseases in the early stages of growth can increase the quality of the final product and prevent the occurrence of permanent damage in large part of farms. Therefore, in this research an intelligent system was designed and developed based on image processing in order to detect and eliminate the disease in the lilium plant leaf, as well as the classification of healthy plants from the unhealthy ones. Accordingly, 20 healthy flowers and 20 unhealthy were evaluated by machine vision system. In order to classify plants, 19 color and morphology parameters of the plant were extracted and the most effective ones (leaf L, leaf a, leaf b, stem L, and stem length) were selected by fuzzy entropy method and these suitable features were grouped by the similarity classifier. As result, the efficiency of the proposed algorithm to diagnose and classify the disease using fuzzy entropy H1, H2 / H3 fuzzy entropy and without applying selection of features method were 96.15, 93.18 and 84.3, respectively. | ||
کلیدواژهها [English] | ||
Plant leaf disease, image processing, fuzzy entropy, similarity classifier | ||
مراجع | ||
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