Accurate Fruits Fault Detection in Agricultural Goods using an Efficient Algorithm
محورهای موضوعی : Information and communication technology in agriculture
حمیدرضا صابرکاری
1
(گروه مهندسی برق، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران)
کلید واژه: image processing, fruit, fault, DCT transform, noise,
چکیده مقاله :
The main purpose of this paper was to introduce an efficient algorithm for fault identification in fruits images. First, input image was de-noised using the combination of Block Matching and 3D filtering (BM3D) and Principle Component Analysis (PCA) model. Afterward, in order to reduce the size of images and increase the execution speed, refined Discrete Cosine Transform (DCT) algorithm was utilized. Finally, for segmentation, fuzzy clustering algorithm with spatial information was applied on the compressed image. Implementation results in MATLAB environment and based on the gathered data by the author showed that the proposed algorithm contains a good capability in de-noising. Also, in the proposed method, identification accuracy of faulty regions in fruit was higher than other methods. The major advantage of the proposed method was its high speed which makes it appropriate for real time applications.
هدف اصلی این مقاله معرفی یک الگوریتم بهینه برای تشخیص خرابی میوهها در محصولات کشاورزی است. ابتدا، تصویر ورودی با استفاده از مدل ترکیبی فیلرینگ تطبیق بلوک سهبعدی و آنالیز مولفههای اصلی نویززدایی میشود. سپس به منظور کاهش ابعاد تصویر و در نتیجه بهبود سرعت پردازش، الگوریتم بهبودیافته تبدیل کسینوسی گسسته مورد استفاده قرار میگیرد. نهایتا الگوریتم خوشهبندی فازی با اطلاعات مکانی بر روی تصویر فشرده شده اعمال میشود. نتایج پیادهسازی در محیط نرمافزار متلب و بر اساس تصاویر جمعآوری شده توسط نویسنده نشان میدهد که الگوریتم پیشنهادی از قابلیت بالایی در حذف نویز برخوردار است. همچنین در این الگوریتم تشخیص نواحی خراب در میوه در مقایسه با سایر روشهای متداول با دقت بالاتری صورت میپذیرد. مزیت عمده الگوریتم پیشنهادی سرعت بالای آن بوده بطوریکه استفاده از آنرا برای کاربردهای بلادرنگ امکانپذیر میسازد.
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