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Proceedings Paper

Express quality control of chicken eggs by machine vision
Author(s): Elena V. Gorbunova; Aleksandr N. Chertov; Vladimir S. Peretyagin; Valery V. Korotaev; Evgeniia A. Arbuzova
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Paper Abstract

The urgency of the task of analyzing the foodstuffs quality is determined by the strategy for the formation of a healthy lifestyle and the rational nutrition of the world population. This applies to products, such as chicken eggs. In particular, it is necessary to control the chicken eggs quality at the farm production prior to incubation in order to eliminate the possible hereditary diseases, as well as high embryonic mortality and a sharp decrease in the quality of the bred young. Up to this day, in the market there are no objective instruments of contactless express quality control as analytical equipment that allow the high-precision quality examination of the chicken eggs, which is determined by the color parameters of the eggshell (color uniformity) and yolk of eggs, and by the presence in the eggshell of various defects (cracks, growths, wrinkles, dirty). All mentioned features are usually evaluated only visually (subjectively) with the help of normalized color standards and ovoscopes. Therefore, this work is devoted to the investigation of the application opportunities of contactless express control method with the help of technical vision to implement the chicken eggs’ quality analysis. As a result of the studies, a prototype with the appropriate software was proposed. Experimental studies of this equipment on a representative sample of eggs from chickens of different breeds have been carried out (the total number of analyzed samples exceeds 300 pieces). The correctness of the color analysis was verified by spectrophotometric studies of the surface of the eggshell.

Paper Details

Date Published: 26 June 2017
PDF: 10 pages
Proc. SPIE 10334, Automated Visual Inspection and Machine Vision II, 103340U (26 June 2017); doi: 10.1117/12.2270411
Show Author Affiliations
Elena V. Gorbunova, ITMO Univ. (Russian Federation)
Aleksandr N. Chertov, ITMO Univ. (Russian Federation)
Vladimir S. Peretyagin, ITMO Univ. (Russian Federation)
Valery V. Korotaev, ITMO Univ. (Russian Federation)
Evgeniia A. Arbuzova, ITMO Univ. (Russian Federation)

Published in SPIE Proceedings Vol. 10334:
Automated Visual Inspection and Machine Vision II
Jürgen Beyerer; Fernando Puente León, Editor(s)

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