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تخمین تازگی گوشت مرغ مبتنی بر تکنیکهای پردازش تصویر و هوش مصنوعی | ||
مهندسی بیوسیستم ایران | ||
مقاله 11، دوره 48، شماره 4، دی 1396، صفحه 491-503 اصل مقاله (1.08 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijbse.2017.63814 | ||
نویسندگان | ||
سودابه فتاحی1؛ امین طاهری گراوند* 2؛ فیض اله شهبازی3 | ||
1گروه مهندسی مکانیک بیوسیستم، دانشگاه لرستان، خرم آباد | ||
2گروه مهندسی مکانیک بیوسیستم دانشگاه لرستان | ||
3دانشگاه لرستان | ||
چکیده | ||
در پژوهش حاضر روشهای نوین نظیر پردازش تصویر و هوش مصنوعی برای ارزیابی سریع، غیر مخرب و آنلاین تازگی گوشت مرغ بکار گرفته شده است. پس از تهیه تصاویر گوشت مرغ و عملیات پیش پردازش، تصاویر به کانالهای رنگی مختلف منتقل و ویژگیهای آماری بافت تصاویر استخراج گردید. عملیات انتخاب ویژگی با ترکیب دو روش الگوریتم ازدحام ذرات و طبقهبند شبکههای عصبی مصنوعی به منظور کاهش حجم محاسبات و ارتقای شاخصهای طبقهبندی انجام شد. با توجه به تعداد ویژگیهای منتخب، تعداد نرونهای موجود در لایه ورودی 22 عدد به دست آمد و تعداد نرونهای موجود در لایه خروجی براساس طبقهبندی تصاویر به صورت 5 کلاس؛ روز اول، روز دوم،...و روز پنجم، 5 عدد تعیین شد. در نهایت ساختار 5-8-22 به عنوان ساختار بهینه طبقهبند مورد نظر حاصل شد. به منظور ارزیابی عملکرد طبقهبند جهت تخمین تازگی گوشت مرغ، شاخصهای آماری نظیر دقت، صحت، حساسیت، اختصاصی بودن و سطح زیر منحنی محاسبه شدند که مقادیر این شاخصها برای طبقهبندی بر اساس ویژگیهای منتخب به ترتیب برابر 92، 02/80، 68/80، 89/94 و83/87 درصد میباشند. نتایج حاصل از این مطالعه نشان میدهد که سامانه پیشنهادی توانایی تشخیص میزان تازگی گوشت مرغ با دقت مناسب را دارد. | ||
کلیدواژهها | ||
گوشت مرغ؛ تشخیص تازگی؛ پردازش تصویر؛ شبکههای عصبی مصنوعی (ANNs)؛ الگوریتم ازدحام ذرات (PSO) | ||
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