نوع مقاله: مقاله کامل پژوهشی

نویسندگان

استادیار، گروه مهندسی مکانیزاسیون کشاورزی، دانشگاه گیلان، رشت، ایران

چکیده

این مطالعه با هدف بررسی بهترین مشخصه‌های استخراج‌شده از تصاویر برای تعیین بهترین روش طبقه‌بندی کیفی چای سبز توسط الگوریتم‌های فراابتکاری انجام شد. 5 طبقۀ مختلف چای سبز مطابق با استاندارد سازمان ملی استاندارد ایران ارزیابی شدند. پس از دریافت تصاویر گروه‌های مختلف چای سبز در رایانه، تعداد 6 بلوک تصویر مربعی از هرکدام از تصاویر رنگی اولیه جدا شدند. این بلوک‌های تصویر از حالت RGB به تصاویر سطح خاکستری تبدیل شدند. فیلتر موجک گسسته هار سطح اول روی تصاویر خاکستری اعمال شد و 4 زیرتصویر موجکی استخراج شدند. ماتریس‌های هم‌رخداد برای هرکدام از تصاویر زیرباند موجک محاسبه شدند و 17 ویژگی بافتی پرکاربرد در مطالعه‌های بافتی تصویر، از تصاویر زیرباندها استخراج شدند (مجموعاً 68 ویژگی بافتی برای هر بلوک تصویر). با استفاده از آنالیز مؤلفه‌های اصلی، تعداد 8 ترکیب ویژگی از ویژگی‌های اولیه تولید شدند و برای جداسازی 5 گروه چای سبز استفاده شدند. نتایج نشان داد که الگوریتم‌هایی از شبکه‌های عصبی مصنوعی، ماشین‌‌بردار پشتیبان و درخت تصمیم، قادر به طبقه‌بندی کیفی چای سبز با دقت بالایی بودند. درحالی‌که شبکۀ بیزین عملکرد قابل‌قبولی نداشت. باتوجه‌به آماره‌های ارزیابی، شبکه‌های عصبی مصنوعی پرسپترون چندلایه (با مقادیر آمارۀ کاپا، ریشۀ میانگین مربعات خطا و دقت طبقه‌بندی به‌ترتیب برابر با 0/9901، 0/420 و 99/17 درصد) به‌عنوان بهترین طبقه‌بندی انتخاب شد. براساس نتایج این پژوهش، استفاده از ماشین بینایی و ویژگی‌های بافتی مستخرج از زیرباندهای موجک تصاویر، روش مناسبی برای طبقه‌‌بندی کیفی چای سبز می‌باشد.

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