Background: Standards of hygiene and health are of major importance in food production, and quality control has become obligatory in this field. Thanks to rapidly developing technologies, it is now possible for automatic and safe quality control of food production. For this purpose, image-processing-based quality control systems used in industrial applications are being employed to analyze the quality of food products. In this study, quality control of chicken (Gallus domesticus) eggs was achieved using a real time image-processing technique.
Results: In order to execute the quality control processes, a conveying mechanism was used. Eggs passing on a conveyor belt were continuously photographed in real time by cameras located above the belt. The images obtained were processed by various methods and techniques. Using digital instrumentation, the volume of the eggs was measured, broken/cracked eggs were separated and dirty eggs were determined. In accordance with international standards for classifying the quality of eggs, the class of separated eggs was determined through a fuzzy implication model.
Conclusion: According to tests carried out on thousands of eggs, a quality control process with an accuracy of 98% was possible.
Keywords: classification of eggs; determination of dirt; fuzzy logic; image processing; quality control.
© 2014 Society of Chemical Industry.