• Journal of Biosystems Engineering
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• v.22 no.1
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• pp.41-48
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• 1997

A nondestructive quality inspection technique using acoustic impulse response method was studied to investigate the feasibility of egg shell inspection. An experimental system was built to generate impact force, to measure the response signal and to analyze the frequency spectrum. This system includes an impulse generating unit, an egg holding seat, a microphone with preamplifier, and a digital oscilloscope connected to Personal Computer by RS-232C interface. The factors such as impulse generating method, egg holding method, and sensor location were evaluated by analyzing the power spectrum density of the measured signal. The results obtained are summarized as follows : 1. From the sampled eggs, the proper conditions for detecting damaged eggs were found as followings; ceramic for the impact ball material, rubber for egg seat material, 20 degrees for an impact angle of pendulum, 10mm for the distance between egg and sensor, the sharp side for impacting part, and 180 degrees for the location of sensor. 2. Examination of the Fourier transformed analysis in beth normal and damaged eggs revealed that those factors such as the resonant frequency, a number of peak frequencies and the magnitude of power spectrum were important to detect damaged eggs.

• Korean Journal of Poultry Science
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• v.22 no.4
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• pp.233-238
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• 1995

A computer vision system was built to generate images of a single, stationary egg. This system includes a CGD camera, a frame grabber, and incandescent back lighting system. Image processing algorithms were developed to inspect egg shell and to sort eggs. Those values of both gray level and area of dark spots in the egg image were used as criteria to detect holes in egg and those values of both area and roundness of dark spots in the egg image were used to detect cracks in egg. For a sample of 300 eggs, this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. The weights of eggs were found to be linear to both the projected area and the perimeter of eggs viewed from above. Those two values were used as criteria to sort eggs. The coefficients of determination(r$^2$) for the regression equations between weights and those two values were 0.967 and 0.972 in the two sets of experiment. Accuracies in grading were found to be 95.6% and 96.7% as compared with results from sizing by electronic weight scale.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.834-841
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• 1996

Egg production in Korea is becoming automated with a large scale farm. Although many operations in egg production have been and cracks are regraded as a critical problem. A computer vision system was built to generate images of a single , stationary egg. This system includes a CCD camera, a frame grabber board, a personal computer (IBM PC AT 486) and an incandescent back lighting system. Image processing algorithms were developed to inspect egg shell and to sort eggs. Those values of both gray level and area of dark spots in the egg image were used as criteria to detect holes in egg and those values of both area and roundness of dark spots in the egg and those values of both area and roundness of dark spots in the egg image were used to detect cracks in egg. Fro a sample of 300 eggs. this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. The weights of eggs were found to be linear to both the projected area and the perimeter of eggs v ewed from above. Those two values were used as criteria to sort eggs. Accuracy in grading was found to be 96.7% as compared with results from weight by electronic scale.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.166-172
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• 2007

Egg quality indices are related with freshness, size of air chamber, loss of weight, and viscosity of the yolk and the protein. However, since the described quality parameters require measured in a destructive way, it is not suitable to inspect the egg quality with complete enumeration. Therefore, this study was performed to investigate the potential of image analysis method for evaluation of internal egg quality. Samples of 90 fresh eggs were collected immediately after laying and stored up to 24 days. Five eggs were randomly drawn from each storage condition (packing vs unpacking) at a regular interval and loss of weight, specific gravity and size of air chamber were measured. The image analysis for nondestructive measurement of size of air chamber was also studied. Results showed that the egg weight and gravity gradually decreased with increasing of storage days, while the size of air chamber linear increased caused by evaporation of water through the shell. A relationship a between conventional method and the image analysis method for measuring the size of air chamber was developed with the correlation coefficient of 0.928. The new finding implied that image analysis might provide a useful nondestructive tool to assess internal egg quality.