استفاده از بینایی کامپیوتر در تشخیص غیرمخرّب زعفران واقعی و تقلبی

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 استاد، مرکز تحقیقات آزمایشگاهی غذا و دارو، سازمان غذا و دارو، وزارت بهداشت، درمان و آموزش پزشکی، تهران، ایران

2 استادیار، اداره آزمایشگاه کنترل غذا و دارو، معاونت غذا و دارو، دانشگاه علوم پزشکی گناباد، گناباد، ایران

3 استادیار، گروه مهندسی برق و کامپیوتر، مجتمع آموزش عالی گناباد

4 دانشجوی دکتری علوم و صنایع غذایی، دانشگاه فردوسی مشهد، مشهد، ایران

10.22048/jsat.2021.299151.1433

چکیده

زعفران یکی از گرانترین ادویه­های جهان محسوب می­شود. زعفران ادویه­ای که بسیار مورد تقلب قرار می­گیرد. توسعه تکنیک­های مبتنی بر ابزار ساده، ارزان قیمت، مناسب و سریع در صنایع غذایی جهت تشخیص تقلّباتی همچون تقلّبات زعفران ضروری است. در پژوهش حاضر، ترکیب پردازش تصویر و روش ماشین بردار پشتیبان (SVM) برای ارزیابی سریع و غیر مخرّب تشخیص زعفران واقعی از زعفران تقلبی به کار رفته است. پس از تهیه تصاویر از توده زعفران خالص و تقلّبی و کلاله­های مجزا، تصاویر وارد مراحل پیش پردازش شدند و در نهایت، ویژگی­های آماری مرتبط با بافت تصاویر و ویژگی­های مورفولوژی شامل 105 ویژگی استخراج شدند. به منظور افزایش سرعت و دقت طبقه­بندی، از روش آنالیز مؤلفه­های اصلی PCA برای کاهش ابعاد ماتریس ویژگی استفاده شد. همچنین طبقه­بندی تصاویر به کمک توابع کرنل مختلف SVM ،به صورت دو کلاس انجام شد. سپس شاخص­های آماری نظیر دقت، صحت، حساسیّت، اختصاصی بودن و سطح زیر منحنی به منظور ارزیابی طبقه­بند محاسبه شدند که مقادیر این شاخص­ها برای طبقه­بندی با کرنل کوبیک SVM برای تشخیص زعفران تقلبی از زعفران واقعی به ترتیب 97، 93، 83، 5/97و 97 درصد بدست آمد. نتایج حاصل از این طبقه­بندی نشان داد که این سیستم به عنوان یک روش هوشمند، سریع، غیرمخرب و دقیق، قابلیت تشخیص زعفران واقعی را از تقلبی  دارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Application of computer vision on non-destructive detection of the authentic and adulterated saffron

نویسندگان [English]

  • Behrouz akbari-adergani 1
  • morteza mohammadzade moghadam 2
  • mehdi Karimi noghabi 2
  • Mojtaba Mohammadpour 3
  • Mohammad Khalilian-Movahhed 4
1 Professor, Food and Drug Laboratory Research Center, Food and Drug Administration, Ministry of Health and Medical Education, Tehran, Iran
2 Assistant Professor, Food and Drug Control Laboratory Office, Food and Drug Deputy, Gonabad University of Medical Sciences, Gonabad, Iran
3 Assistant Professor, Department of Electrical & Computer Engineering, Faculty of Engineering, University of Gonabad, Gonabad, Iran
4 PhD Student, Department of Food Science and Technology, Ferdowsi University of Mashhad, Mashhad, Iran
چکیده [English]

Saffron is one of the most expensive spices in the world. Saffron is a spice that is widely cheated. The development of techniques based on simple, inexpensive, appropriate and fast tools in the food industry is essential for detecting adulteration such as saffron adulterated. In the present study, the combination of image processing and Support vector machine (SVM) method has been used for fast and non-destructive evaluation of distinguishing authentic saffron from adulterated saffron. After preparing images from pure and counterfeit saffron and separate stigmas, the images entered the pre-processing stages and finally, statistical features related to the texture of the images and morphological features including 105 features were extracted. In order to increase the speed and accuracy of classification, PCA principal component analysis method was used to reduce the properties of the feature matrix. Also, the images were classified into two classes using different SVM kernel functions. Also, the images were classified into two classes using different SVM kernel functions. Then statistical indicators such as accuracy, precision, sensitivity, specificity and AUC were calculated to evaluate the classification. The values of these indices for classification with SVM cubic kernel for authentic saffron were 97, 98, 99, 93 and 97%, and for adulterated saffron, 97, 93, 83, 97.5 and 97% were obtained, respectively. The results of this classification showed that this system, as an intelligent, fast, non-destructive and accurate method, has the ability to distinguish the authentic saffron from adulterated saffron.

کلیدواژه‌ها [English]

  • Saffron
  • Fraud
  • image processing
  • SVM
 
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