Egg weighing and classification are among the most significant phases
done in egg processing by industries which are tedious if done manually by
poultry owners, and egg inspectors and graders.
This study presented an alternative way of estimating chicken egg weight
through computer vision minimizing human interaction during the process. In
this study, fifteen eggs of white leghorn chicken layers of different sizes
were tested. The eggs’ image was captured using an inexpensive yet reliable
webcam which was then loaded onto the MatLab workspace for image processing and
further image analysis. The center of gravity of the image was determined, and
the extraction of minor axis length and major axis length followed. The
obtained values were used to compute the egg’s weight mathematically. Through
the different image processing methods, image dimensions were extracted and
used to calculate the desired output. The results of this study showed 96.31%
accuracy in estimating the egg’s weight and classification validated by manual
egg weighing and classification procedure.
Birincil Dil | İngilizce |
---|---|
Konular | Gıda Mühendisliği |
Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 20 Eylül 2018 |
Gönderilme Tarihi | 1 Nisan 2018 |
Kabul Tarihi | 11 Mayıs 2018 |
Yayımlandığı Sayı | Yıl 2018 |
International Journal of Agriculture, Environment and Food Sciences dergisinin içeriği, Creative Commons Alıntı-GayriTicari (CC BY-NC) 4.0 Uluslararası Lisansı ile yayınlanmaktadır. Söz konusu telif, üçüncü tarafların içeriği uygun şekilde atıf vermek koşuluyla, ticari olmayan amaçlarla paylaşımına ve uyarlamasına izin vermektedir. Yazarlar, International Journal of Agriculture, Environment and Food Sciences dergisinde yayınlanmış çalışmalarının telif hakkını elinde tutar.
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