کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6390994 | 1628412 | 2015 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Assessment of grape cluster yield components based on 3D descriptors using stereo vision
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
دانش تغذیه
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Assessment of grape cluster yield components based on 3D descriptors using stereo vision Assessment of grape cluster yield components based on 3D descriptors using stereo vision](/preview/png/6390994.png)
چکیده انگلیسی
The purpose of this paper is to propose a three-dimensional computer vision approach to assessing grape yield components based on new 3D descriptors. To achieve this, firstly a partial three-dimensional model of the grapevine cluster is extracted using stereo vision. After that a number of grapevine quality components are predicted using SVM models based on new 3D descriptors. Experiments confirm that this approach is capable of predicting the main cluster yield components, which are related to quality, such as cluster compactness and berry size (R2 > 0.80, p < 0.05). In addition, other yield components: cluster volume, total berry weight and number of berries, were also estimated using SVM models, obtaining prediction R2 of 0.82, 0.83 and 0.71, respectively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Food Control - Volume 50, April 2015, Pages 273-282
Journal: Food Control - Volume 50, April 2015, Pages 273-282
نویسندگان
E. Ivorra, A.J. Sánchez, J.G. Camarasa, M.P. Diago, J. Tardaguila,