کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11263045 | 1797863 | 2018 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Semantic labeling and reconstruction of grape bunches from 3D range data using a new RGB-D feature descriptor
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In the context of grapevine breeding, high precision and automated phenotyping plays an important role in order to screen breeding material (e.g. seedlings) or to characterize genetic repositories with high-throughput. Grape bunches hereby reveal a large variability regarding size, shape, compactness and color. We design and evaluate a new RGB-D descriptor for the semantic labeling of grape bunches. For this, we examine RGB and HSI color spaces and combine them with Fast-Point-Feature Histograms. With the best combination of FPFHs and the hue channel we achieve an average F-value of 88.61%, outperforming classical descriptors like PFHRGB and SHOTColor by at least 8%. Additionally, we show a new method for the derivation of parametric reconstructions of the elliptical berries based on a least squares fitting, yielding Pearson correlation coefficients of 0.8 and 0.9 for the main diameters of the berries.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 155, December 2018, Pages 96-102
Journal: Computers and Electronics in Agriculture - Volume 155, December 2018, Pages 96-102
نویسندگان
Jennifer Mack, Frank Schindler, Florian Rist, Katja Herzog, Reinhard Töpfer, Volker Steinhage,