DEVELOPMENT OF IMAGING TECHNOLOGY FOR FOOD SAFETY AND SECURITY
Location: Quality and Safety Assessment Research Unit
Title: Modified Pressure System for Imaging Egg Cracks
Submitted to: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE)
Publication Type: Proceedings
Publication Acceptance Date: June 30, 2008
Publication Date: June 30, 2008
Citation: Lawrence, K.C., Yoon, S.C., Jones, D.R., Heitschmidt, G.W., Park, B., Windham, W.R. 2008. Modified Pressure System for Imaging Egg Cracks. Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE).p. 1-14.
Interpretive Summary: Interpretive Summary
Cracks in shell eggs are one of the defects that are used in grading shell eggs. Graders with the Agricultural Marketing Service (AMS) are having trouble identifying very small hair-line cracks, know as micro-cracks, which initially are very small, but grow over time as the egg cools and undergoes thermal stresses. We originally developed an imaging system that identifies cracks, including micro-cracks, with a novel imaging system on single shell eggs. We have now expanded the system to image 15 eggs at a time. The key to the system is a vacuum chamber that allows us to pull a very rapid but low negative pressure on a shell egg. The system first takes an image of the eggs under atmospheric pressure and then takes another image while the eggs are under atmospheric pressure and uses the ratio of those two images to detect the cracks. In a study of 1000 eggs (352 cracked and 648 intact eggs), the system correct identified 350 cracked eggs (99.4%) and 646 intact eggs (99.7%) for an overall accuracy of 99.6%. In comparison, the AMS human graders correctly identified 302 cracked eggs (85.8%) and 640 intact eggs (98.8%) for a total accuracy of 94.2%. An international patent on the system was filed but further automation of the system is needed.
One aspect of grading table eggs is shell checks or cracks. Currently, USDA voluntary regulations require that humans grade a representative sample of all eggs processed. However, as processing plants and packing facilities continue to increase their volume and throughput, human graders are having difficulty matching the pace of the machines. Additionally, some plants also have a problem with micro-cracks that the graders often miss because they are very small and hard to see immediately post-processing but grow and become readily apparent before they reach market. An imaging system was developed to help the grader detect these small micro-cracks. The imaging system utilized one image captured at atmospheric pressure and a second at a slight negative pressure to enhance the crack and make detection much easier. A simple image processing algorithm was then applied to the ratio of these two images and the resulting image, containing both cracked and/or intact eggs were color-coded to simplify identification. The imaging system was capable of imaging 15 eggs in about ¾ second and the algorithm processing took about another 10 seconds. These times could easily be reduced with a dedicated, multi-threaded computer program. In analyzing 1000 eggs, the system was 99.6% accurate overall with only 0.3% false positives compared to 94.2% accurate overall for the human graders with 1.2% false positives. An international patent on the system was filed and further automation of the system is needed.