تشخیص فلفل دلمه‌ای با استفاده از هیستوگرام ویژگی سریع نقطه و یادگیری بدون نظارت

ماشین های کشاورزی

مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 11 خرداد 1404   

نوع مقاله: مقاله پژوهشی انگلیسی

شناسه دیجیتال (DOI): 10.22067/jam.2023.83054.1174

نویسندگان

امید دوستی ایرانی^* ؛ محمدحسین آق خانی؛ محمودرضا گلزاریان

گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه فردوسی مشهد، مشهد، ایران

چکیده

برداشت رباتیک محصولات کشاورزی فرآیندی مهم و موثر برای تولید میوه سالم، کاهش هزینه‌های برداشت و افزایش بهره‌وری است. با پیشرفت بینایی ماشین، استفاده از اطلاعات سه‌بعدی به‌جای اطلاعات دوبعدی در حال گسترش است. با این حال، برداشت فلفل دلمه‌ای به‌عنوان یکی از محصولات گلخانه‌ای، به دلیل دقت پایین سنسورهای دوبعدی با چالش‌هایی مواجه است. هدف این مطالعه توسعه یک الگوریتم بینایی ماشین بدون نظارت برای تشخیص فلفل دلمه رنگی با استفاده از ترکیبی از ویژگی‌های هندسی (هیستوگرام ویژگی نقطه سریع- FPFH) و ویژگی‌های رنگی (HSV) است. تصاویر عمق با استفاده از حسگر Kinect-v2 دریافت و مدل سه‌بعدی بازسازی شده است. پس از استخراج ویژگی‌های هندسی و رنگ، داده‌ها با استفاده از روش زیر نمونه‌گیری و با اعمال معیار Z-score برای فیلتر کردن نویزها، پیش‌پردازش شدند. تحلیل مؤلفه اصلی (PCA) برای کاهش ابعاد ویژگی‌ها استفاده شد و مدل خوشه‌بندی k-means با استفاده از شش ویژگی هندسی و سه ویژگی رنگ، به داده‌ها اعمال شد. ضریب سیلوئت برای ارزیابی کیفیت خوشه‌بندی استفاده شد و ارزیابی انسانی نشان داد که الگوریتم با دقت 95.10 درصد قادر به تشخیص فلفل دلمه‌ای است.

کلیدواژه‌ها

برداشت رباتیک؛ بینایی ماشین؛ فلفل دلمه‌ای؛ هیستوگرام ویژگی سریع نقطه؛ K-means

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