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A Multi-Flow Production Line for Sorting of Eggs Using Image Processing.

Fatih AkkoyunAdem OzcelikIbrahim ArpaciAli ErcetinSinan Gucluer
Published in: Sensors (Basel, Switzerland) (2022)
In egg production facilities, the classification of eggs is carried out either manually or by using sophisticated systems such as load cells. However, there is a need for the classification of eggs to be carried out with faster and cheaper methods. In the agri-food industry, the use of image processing technology is continuously increasing due to the data processing speed and cost-effective solutions. In this study, an image processing approach was used to classify chicken eggs on an industrial roller conveyor line in real-time. A color camera was used to acquire images in an illumination cabinet on a motorized roller conveyor while eggs are moving on the movement halls. The system successfully operated for the grading of eggs in the industrial multi-flow production line in real-time. There were significant correlations among measured weights of the eggs after image processing. The coefficient of linear correlation (R 2 ) between measured and actual weights was 0.95.
Keyphrases
  • deep learning
  • convolutional neural network
  • machine learning
  • artificial intelligence
  • magnetic resonance imaging
  • big data
  • optical coherence tomography
  • risk assessment