کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8878695 | 1645590 | 2017 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Application of computer vision and support vector regression for weight prediction of live broiler chicken
ترجمه فارسی عنوان
استفاده از دیدگاه رایانه و رگرسیون بردار پشتیبانی برای پیش بینی وزن مرغ زنده جوجه های گوشتی
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کلمات کلیدی
پردازش تصویر، رگرسیون بردار پشتیبانی، برآورد وزن، جوجه گوشتی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم زراعت و اصلاح نباتات
چکیده انگلیسی
A very important ingredient in the recipe for a productive broiler breeder flock is the collection of frequent and accurate body weights. To achieve this goal in this paper image processing and support vector regression (SVR) were used as a non-invasive method. An ellipse fitting algorithm using generalized Hough transform was performed to localize chickens within the pen and the head as well as the tail of chickens was removed using Chan-Vese method. After that from broiler images six features were extracted, namely area, convex area, perimeter, eccentricity, major axis length and minor axis length. According to statistical analysis between weight estimation of SVR and manual measurement of birds up to 42 days, no significant difference was observed (PÂ >Â 0.05). The RMSE (root mean square error), MAPE (mean absolute percentage error) and the R2 (correlation coefficient) value of SVR algorithm were 67.88, 8.63% and 0.98, respectively. This shows that machine vision along with SVR could promisingly estimate the weight of life broiler chickens.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering in Agriculture, Environment and Food - Volume 10, Issue 4, October 2017, Pages 266-271
Journal: Engineering in Agriculture, Environment and Food - Volume 10, Issue 4, October 2017, Pages 266-271
نویسندگان
Somaye Amraei, Saman Abdanan Mehdizadeh, Somayeh Sallary,