با همکاری انجمن علمی گیاهان دارویی ایران

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، گروه مهندسی کامپیوتر، موسسه آموزش عالی هاتف، زاهدان

2 استادیار، گروه مهندسی کامپیوتر، دانشکده فنی و مهندسی، دانشگاه ولایت، ایرانشهر

3 مربی، گروه مهندسی کامپیوتر، دانشکده مهندسی کامپیوتر و صنایع، دانشگاه صنعتی بیرجند، بیرجند

چکیده

 زعفران یکی از با ارزش­ترین گیاهان زراعی موجود در روی کره زمین می­باشد، که این گیاه به عنوان گران­ترین محصول کشاورزی و دارویی جهان جایگاه ویژه ای در بین محصولات صنعتی و صادراتی کشور ایران دارد. یکی از مشکلاتی که در تولید این گیاه وجود دارد، برداشت به موقع آن از روی زمین و جداسازی کلاله (شاخه) های قرمز زعفران از بقیه قسمت­های گل زعفران می باشد، چرا که عمدتاً گل­های زعفران در یک بازه زمانی بسیار کوتاه به ثمر می­رسند و همچنین برداشت و جداسازی آن در این بازه زمانی محدود بسیار اهمیت دارد. در این پژوهش، سعی شده­است که با استفاده از تکنیک­های پردازش تصویر به بحث و بررسی نحوه شناسایی گل زعفران در روی زمین پرداخته شود. در مرحله اول برای شناسایی گل زعفران از تبدیلات فضاهای رنگی استفاده نموده، سپس از طریق هیستوگرام و آستانه مینیمم نسبت به بخش­بندی و حذف پیکسل­های اضافی اقدام شده است. بدین­منظور، برای شناسایی گل از تبدیل فضای RGB به فضای YCbCr و برای تشخیص سایر اشیاء موجود در تصویر از ترکیب فضاهای رنگی  HSI  و YCgCr استفاده و از هیستوگرام مؤلفه Cb برای تشخیص اولیه گل زعفران بهره برده­اند. سپس، برخی از پیکسل­هایی که به اشتباه تشخیص داده شده­اند، با کمک مقدار آستانه حذف گردیده اند. در مرحله بعدی، برگ­های سوزنی­شکل گیاه زعفران، که بر روی گل­ها قرار گرفته­اند با استفاده از عملیات مورفولوژیک الگوریتم پیشنهادی ترمیم و روی­هم ­افتادگی گل­ها بازسازی شده است. در گام بعدی، نوع گل زعفران (غنچه، شکسته، گل باز شده) تعیین گردیده و قابل برداشت بودن و یا مناسب نبودن گل زعفران برای برداشت تعیین شده است. در انتها مرکز گل­هایی که قابل برداشت تعیین شده اند، مشخص و در اختیار ربات برداشت زعفران قرار می­گیرد. میانگین نتایج ارزیابی، با معیار دقت، فراخوانی، F-measure، درستی و ضریب همبستگی به ترتیب 79/99، 42/99، 60/99، 91/99 و 50/99 برای روش پیشنهادی حاصل شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Locating and Recognizing of Saffron Flowers using Image Processing

نویسندگان [English]

  • Mostafa Dehbashi 1
  • Amir Rajaei 2
  • Hossein KardanMoghadam 3

1 Department of Computer Engineering, Hatef Higher Education Institution, Zahedan

2 Department of Computer Engineering, Velayat University, Iranshahr

3 Department of Computer Engineering, Birjand University of Technology, Birjand

چکیده [English]

Saffron is one of the most valuable crops on the planet and the most expensive agricultural and medicinal product globally; this plant has a special place among the industrial and export products of Iran. One of the challenges in the production of this plant is timely harvest from the ground as well as red stigmas (branches) separating from other parts of saffron because the flowers are harvested in a brief period. Further, harvesting and separating at a limited time is a critical point. This research has been tried with the help of image processing techniques to discuss and recognize saffron flowers and how to identify them on the ground. In the first step, saffron flowers are recognized by transforming colored spaces. Then, the histogram and the minimum threshold are used to segment and remove extra pixels. For this purpose, to identify flowers, RGB space is converted to YCbCr space, and the combination of HSI and YCbCr color space is used to distinguish other objects in the image; also, a histogram of Cb component for early identification of saffron flowers are used. Then, those pixels which are misidentified are removed by the threshold value. Next step, the saffron flower needle-shaped leaves that are placed on the flowers are restored by morphological operation of the proposed method, and the flowers that overlap are removed. Then, the type of saffron flower (bud, broken, open flower) is determined, and the ability of harvest or suitability of saffron flowers for harvesting has been determined. Finally, the flower center that can be harvested is recognized and used by the saffron harvesting robot. Average results with respect to the accuracy, recall, F-measure, correctness, and correlation coefficient were 99.79, 99.42, 99.60, 99.91, and 99.50 achieved by the proposed method, respectively.

کلیدواژه‌ها [English]

  • Flag
  • Morphological Operation
  • Color space
  • Flower bud
  • Threshold value
  • Histogram
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