Dirt detection on brown eggs by means of color computer vision

Poultry Science

Volumn 84, Issue 10, 2005, Pages 1653-1659

  Mertens, Kristof ^a   De Ketelaere, B ^a   Kamers, B ^a   Bamelis, F R ^a   Kemps, B J ^a   Verhoelst, E M ^a   De Baerdemaeker, J G ^a   Decuypere, E M ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Brown eggs; Computer vision; Dirt detection; Egg grading

Indexed keywords

PIERIS BRASSICAE;

URIC ACID;

ANIMAL; ARTICLE; ARTIFICIAL INTELLIGENCE; BLOOD; CHICKEN; COLOR; COMPUTER PROGRAM; EGG; FECES; FOOD CONTAMINATION; FOOD HANDLING; LIGHT; METHODOLOGY; STANDARD;

ANIMALS; ARTIFICIAL INTELLIGENCE; BLOOD; CHICKENS; COLOR; EGGS; FECES; FOOD CONTAMINATION; FOOD HANDLING; LIGHT; SOFTWARE; URIC ACID;

EID: 33644815231     PISSN: 00325791     EISSN: 15253171     Source Type: Journal    
DOI: 10.1093/ps/84.10.1653     Document Type: Article

References (17)

1. Bliss, G. N. 1973. Crack detector. United States Patent No. 3744299. U.S. Patent Office, Washington, D.C.
2. Brant, A. W., K. H. Norris, and G. Chin. 1952. A spectrophotometric method for detecting blood in white-shell eggs. Poult. Sci. 32:357-363.
3. Coucke, P. 1998. Assessment of some physical egg quality parameters based on vibration analysis. Ph.D. Thesis. Katholieke Univ., Leuven, Belgium.
4. De Ketelaere, B., P. Coucke, and J. G. De Baerdemaeker. 2000. Eggshell crack detection based on acoustic resonance frequency analysis. J Agric. Eng. Res. 76:157-163.
5. De Reu, K., K. Grijspeerdt, M. Heyndrickx, M. Uyttendaele, and L. Herman. 2005. The use of total earobic and Gram-negative flora for quality assurance in the production chain of consumption eggs. Food Control 16:147-155.
6. Elster, R. T., and J. W. Goodrum. 1991. Detection of cracks in eggs using machine vision. Trans. ASAE 30:307-312.
7. García-Alegre, M. C., J. Enciso, A. Ribeiro, and D. Guinea. 1997. Towards an automatic visual inspection of eggshell defects. Pages 51-66 in Proc. Int. Workshop on Robotics and Automated Machinery for Bio-Productions, Gandia, Spain.
8. García-Alegre, M. C., A. Ribeiro, D. Guinea, and G. Cristobal. 2000. Color index analysis for automatic detection of eggshell defects. Pages 380-387 in Proc. SPIE 3966:380-387.
9. Gielen, R. M. A. M., L. P. De Jong, and H. M. M. Kerkvliet. 1979. Electrooptical blood-spot detection in intact eggs. Trans. Instrument. Measur. 28:177-183.
10. Goodrum, J. W., and R. T. Elster. 1992. Machine vision for crack detection in rotating eggs. Trans. ASAE. 35:1323-1328.
11. Han, Y. J., and Y. Feng. 1994. Egg shell inspection using global image analysis. Appl. Eng. Agric. 10:109-114.
12. Moayeri, H. 1996. Probe, inrichting en werkwijze voor het testen van eieren. Patent no. 1000177, The Netherlands.
13. Oosterwoud, A., J. E. R. Frijters, and C. Davids. 1976. Some factors affecting mass candling performance of eggs. Br. Poult. Sci. 17:249-260.
14. Patel, V. C., R. W. McClendon, and J. W. Goodrum. 1994a. Crack detection in eggs using computer vision and neural networks. Artif. Intell. Appl. 8:21-31.
15. Patel, V. C., R. W. McClendon, and J. W. Goodrum. 1994b. Detection of blood spots and dirt stains in eggs using computer vision and neural networks. Report No. 94-G-034. Pages 833-834 in Proc. Int. Conf. Agric. Eng., Milan, Italy.
16. Patel, V. C., R. W. McClendon, and J. W. Goodrum. 1998. Color computer vision and artificial neural networks for the detection of defects in poultry eggs. Artif. Intell. Rev. 12:163-176.
17. Ribeiro, A., M. C. García-Alegre, D. Guinea, and G. Cristobal. 2000. Automatic rules generation by G.A. for eggshell defect classification. Eur. Congr. Comput. Methods Appl. Sci. Eng., Barcelona, Spain.