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تعیین مناسبترین فضای رنگی به منظور تعیین تنش آبی در گیاهان گلخانه‌ای به صورت هوشمند (مطالعه موردی: حُسنِیوسف) | ||
| مهندسی بیوسیستم ایران | ||
| مقاله 3، دوره 48، شماره 4، دی 1396، صفحه 407-418 اصل مقاله (1.19 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijbse.2017.63806 | ||
| نویسندگان | ||
| مریم نداف زاده؛ سامان آبدانان مهدی زاده* | ||
| دانشگاه رامین خوزستان | ||
| چکیده | ||
| تخمیندقیق میزان آب مصرفی گیاه به عوامل بسیاری وابسته است که درصد پوشش سبز گیاه یکی از مؤثرترین پارامترها می‌باشد. از پردازش تصاویر دیجیتال و بینایی ماشین میتوان به منظور اندازهگیری این پارامتر در برنامههای مدیریت آب در کشاورزی به طور گسترده استفاده نمود. در این پژوهش مجموعهای از تصاویر گیاه زینتی حُسنِیوسف در دو وضعیت (شاداب و پژمرده) جهت تجزیه و تحلیل پیکسلها و مقایسه فضاهای رنگ پیشنهاد شده با هدفِ تشخیص نیاز آبی گیاه مورد بررسی قرار گرفتند؛ فضاهای رنگی مورد بررسی عبارتند از: RGB، rgb، XYZ، Lab، UVL، HSV، HLS، YCbCr، YUV، TSL و.I1I2I3 هر فضای رنگی شرایط مختلفی از احتمال توزیع یک گروه رنگ را ارائه میدهد، بدین ترتیب پس از بررسی فضاهای رنگی با توجه به نتایج آنالیز آماری در سطح احتمال 5% و با کمک ترسیم دادهها و مقایسه بصری آنها، مناسبترین فضاهای رنگی انتخاب گردید. نهایتاً فراوانی شدتهای فضای رنگی مطلوب جهت آموزش طبقهبند بیز مورد استفاده قرار گرفتند که در این حالت طبقهبند بیز با دقت کلی 11/83 درصد دو وضعیت شاداب و پژمرده گیاه را از یکدیگر تشخیص داد. در نتیجه بر اساس اطلاعات حاصل از نمودارهای هیستوگرام تصاویر (فراوانی سطوح شدت تصاویر) وضعیت نیاز گیاه به آبیاری قابل تشخیص می‌باشد. | ||
| کلیدواژه‌ها | ||
| فضاهای رنگی؛ پردازش تصاویر دیجیتال؛ آبیاری؛ پژمردگی؛ طبقه بند بیز | ||
| عنوان مقاله [English] | ||
| Determination of the most suitable color space for intelligent water stress discrimination for plants inside the greenhouse (Case Study: Coleus) | ||
| نویسندگان [English] | ||
| Maryam Nadafzadeh؛ Saman Abdanan Mehdizadeh | ||
| University of Khuzestan, Ahvaz, Khuzestan | ||
| چکیده [English] | ||
| A precise estimation of required water for plant depends on many factors, among which the percentage of ground cover is a key parameter. Digital image processing and machine vision can be widely used to obtain this parameter in irrigation management applications. The aim of this study was to recognize the required water for plants based on color parameters of plants’ ground cover; therefore, different color spaces (RGB, rgb, XYZ, HSV, HLS, L*a*b, L*u*v*, YCbCr, YUV, TSL and I1I2I3) were applied on the set of ornamental shrub images with the scientific name of Plectranthusscutellarioides in two positions (fresh and wilting).Each color space demonstrated different probability distribution ofa given color class corresponded to two plant conditions (fresh and wilting). Thus, after examining the color spaces, both statistically and visually, the suitable color spaces were selected. Finally, histograms of suitable color spaces have been used to train the Bayesian Classifier. The Bayesian classifier detected two conditions of plant (fresh and wilting) with precision 83.11%. In general, on the basis of information obtained from images histograms, (frequency of pixels’ intensity) plantswater status for irrigationschedulingwas recognizable. | ||
| کلیدواژه‌ها [English] | ||
| Color Spaces, Digital images processing, Irrigation, Wilting, Bayesian classifier | ||
| مراجع | ||
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