کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6539285 | 1421096 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fast Bi-dimensional empirical mode decomposition as an image enhancement technique for fruit defect detection
ترجمه فارسی عنوان
تجزیه حالت تجربی سریع دو بعدی به عنوان یک روش بهبود تصویر برای تشخیص نقص میوه
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کلمات کلیدی
تجزیه حالت تجربی، افزایش کیفیت عکس، روشن ساختار کاستی، میوه،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Image enhancement is critical to detection of fruit defects by imaging techniques. Vignetting and noise are major image artifacts, which can seriously affect image segmentation results, especially in inspecting the curved-surface objects like fruit. It is common to use a calibration object or a mathematic model to reduce the vignetting effect in defect detection, but the approach is often cumbersome, inflexible, and difficult to achieve desired results. In this study, a new image enhancement method based on bi-dimensional empirical mode decomposition (BEMD) of images was proposed to isolate and subsequently remove the effects of vignetting and noise by means of selective image reconstruction. The new BEMD method, along with three other BEMD methods, was first tested on decomposing a synthetic image with artificially added vignetting and noise. The BEMD was found to be the most efficient for image decomposition in terms of computation time, and also give high-quality reconstructed images. Experiments were further conducted by applying the BEMD to the direct and amplitude component images of apple samples with subsurface bruising and surface defects, which were acquired by using a structured-illumination reflectance imaging (SIRI) system. BEMD effectively reduced the image vignetting and greatly enhanced the defect features of the apples, based on both visual inspection and quantitative evaluation. BEMD offers an effective tool for enhancing SIRI images, and it is also promising for image enhancement with other imaging modalities for fruit defect detection.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 152, September 2018, Pages 314-323
Journal: Computers and Electronics in Agriculture - Volume 152, September 2018, Pages 314-323
نویسندگان
Yuzhen Lu, Renfu Lu,