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| International Agrophysics |
| wydawca: | Instytut Agrofizyki
im. B. Dobrzańskiego
PAN
w Lublinie |
| ISSN: |
0236-8722 |
vol. 26, nr. 3 (2012)
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poprzedni artykuł wróć do listy artykułów następny artykuł
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Fresh egg mass estimation using machine vision technique
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| (pobierz wersję PDF )
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V. Asadi1, M. H. Raoufat2, M. Nassiri2
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1 Department of Mechanical Engineering, Majlesi Branch, Islamic Azad University, Isfahan, Iran |
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2 Department of Agricultural Engineering, Shiraz University, Shiraz, Iran |
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vol. 26 (2012), nr. 3,
pp. 229-234
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streszczenie
In the present study a machine vision system was
developed for estimating the mass of eggs arranged in a single
array. A grabber frame equipped with a mirror was developed for
positioning the eggs. Therefore, two images could be captured
from each egg. Images were then processed by Matlab software.
Six algorithms were developed to extract eggs features such as
minimum, maximum and effective radii, perimeter and the frontal
area from each image. The eggs were also weighed by a sensitive
digital scale. Seventy percent of data after discarding the outliers
were used to establish some models, and the remaining was used to
verify the final model. The results showed that egg mass estimation
can be accurate by using two perpendicular views of each egg.
Amongst the models, one with predictors of area and effective radius
was found to be the best. A high correlation coefficient was
observed between eggs mass measured and predicted by the model,
with an accuracy of about 95%.
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słowa kluczowe
egg, fresh mass, machine vision
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