• Journal of Biosystems Engineering
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• v.24 no.3
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• pp.253-258
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• 1999

This study was conducted to develop an automatic egg inspection system for detecting creaked eggs based on acoustic impulse response. This system includes a sound generator, a sound sensor with signal conditioner, and a computer. The sound generator that hit the sharp of the dull edges of an egg was constructed with a ceramic ball pendulum attached to a rotary type solenoid. The signal conditioner included a pre-amplifier and a digital signal processing (DSP) board. The parameters for distinguishing cracked and normal eggs were the area, the geometric centroid and the resonance frequency of power spectrum of the acoustic signal generated. An algorithm for on-line detection of the continuous transferring eggs was developed. The performance tests resulted with 91% success rate to separate cracked and normal eggs at the rate of 1 second per an egg.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.12a
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• pp.401-406
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• 1998

• Food Science and Preservation
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• v.20 no.1
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• pp.69-75
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• 2013

This study was conducted to investigate the reliability of automatic cracked and bloody egg detector according to the age of the hens and the level of the detector. The results of this study are expected to be helpful in the implementation of the Korean egg grading system, which is expected to improve egg quality for consumers. An official egg grader randomly selected 1,000 eggs for each experiment (total 36,000 eggs), ran them through the automatic detector, and conducted labor inspection using the eggs that were classified by the detector as cracked, bloody, and normal eggs. The results showed that more cracked eggs were laid by hens aged 40-60 weeks than by hens aged 30 weeks (p<0.05). Also, when the detector level increased from four to seven (i.e., when it became less sensitive), its cracked eggs detection rate dropped, and the total rate of cracked eggs was consistent after the labor inspection of the classified eggs. The automatic detector achieved over 97 percent accuracy. The bloody eggs constituted only 0.005 percent of all the samples, and all the detector-detected eggs were bloody eggs after the labor inspection of both the bloody and normal egg lines. Therefore, it can be concluded that the automatic cracked and bloody egg detector was reliable and can be used in the egg grading system. Considering that cracked eggs should be less than 9 percent of first-grade eggs in the present egg grading system, the use of an automatic crack detector may help provide better-quality eggs to consumers by producing less than 5.5 percent cracked 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.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.348-354
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• 2008

Egg grading is determined by exterior and interior quality. Among the evaluation methods for the egg quality, a candling method is common to identify eggs with cracked shells and interior defects. But this method is time-consuming and laborious. In addition, practically, it is challenging to detect hairline and micro cracks. In this study, an on-line inspection system based on acoustic resonance frequency analysis was developed to detect hairline cracks on eggshells. A roller conveyor was used to transfer eggs along one lane to the impact position where each of eggs rotated by the roller was excited with an impact device at four different locations on the eggshell equator. The impact device was consisted of a plastic hammer and a rotary solenoid. The acoustic response of the egg to the impact was measured with a small condenser microphone at the same position as the impact device was installed. Two acoustic parameters, correlation coefficient for normalized power spectra and standard deviation of peak resonant frequencies, were used to detect cracked eggs. Intact eggs showed relatively high correlations among the four normalized power spectra and low standard deviations of the four peak resonant frequencies. On the other hand, cracked eggs showed low correlations and high standard deviations as compared to the intact. This method allowed a crack detection rate of 97.6%.