ترکیب بینی الکترونیک و بینایی کامپیوتر برای تشخیص تقلب روغن لامپانت در روغن زیتون فرابکر با استفاده از الگوریتم‌های یادگیری ماشین
الموضوعات : Multimedia Processing, Communications Systems, Intelligent Systemsمهسا میرحسینی مقدم 1 , محمدرضا یمقانی 2 , عادل بخشی پور 3
1 - دانشجوی دکتری، گروه مهندسی کامپیوتر، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران
2 - استادیار، گروه مهندسی کامپیوتر، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران
3 - استادیار، گروه مهندسی بیوسیستم، دانشکده علوم کشاورزی دانشگاه گیلان، رشت، ایران
الکلمات المفتاحية: تقلب, کمومتریک, بینی الکترونیک, پردازش تصویر, همجوشی داده¬ها,
ملخص المقالة :
روغن زیتون یک محصول با اررزش غذایی محسوب می¬شود که تقلب در آن با روغن¬های کم کیفیت رو به افزایش است. روش‌های مختلفی برای ارزیابی کیفیت روغن زیتون وجود دارد.در این پژوهش چهار سطح تقلب (5، 10، 15 و 20 درصد ناخالصی) با اختلاط روغن لامپانت در روغن زیتون فرابکر ایجاد شد، و نمونه های خالص و تقلبی توسط یک سامانه بینی الکترونیکی با 13 حسگر گازی و یک سامانه بینایی کامپیوتری مورد تجزیه و تحلیل قرار گرفتند. این صحت در هنگام استفاده از مؤلفه¬های اصلی استخراج شده از ویژگی¬های تصویر برابر با 100 درصد بود. نتایج نشان داد که الگوریتم حداقل مربعات جزئی (PLS) قادر به پیش¬بینی میزان ناخالصی روغن لامپانت در روغن زیتون فرابکر با ضریب تبیین (R2) آموزش و اعتبارسنجی به ترتیب برابر با 8565/0 و 7858/0 بود. این مقادیر در هنگام استفاده از ویژگی¬های رنگی به ترتیب برابر با 6983/0 و 4936/0بودند که نشان داد استفاده از داده¬های حاصل از بوی روغن روش مناسب¬تری نسبت به رنگ برای تخمین نرخ ناخالصی لامپانت در روغن زیتون فرابکر است. از سوی دیگر، ادغام داده‌های استخراج‌شده از عطر و رنگ برای تعیین میزان ناخالصی، دقت پیش‌بینی را به طور قابل توجهی افزایش داد. مقدار R2 آموزش و اعتبارسنجی مدل PLS با داده¬های ترکیبی برای پیش¬بینی اختلاط روغن لامپانت برابر با 9266/0 و 9184/0 به دست آمد. براساس نتایج این پژوهش می¬توان از سامانه ترکیبی بینی و بینایی الکترونیک برای توسعه یک سامانه غیر مخرب و دقیق برای پایش تقلب در روغن زیتون استفاده کرد.
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