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Research on the nondestructive detection of egg freshness based on image processing
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: 2018 ASABE Annual International Meeting 1800829.(doi:10.13031/aim.201800829)
Authors: Haodong Qin, Wei Wang, Xuan Chu, Hongzhe Jiang, Xin Zhao, Beibei Jia, Yi Yang, Daniel Kimuli, Aijun Dong, Bo Wang, Xiwei Bai
Keywords: Feature extraction, freshness of eggs, image processing.
Abstract. Freshness is one of the important indexes of the internal quality of eggs, which affects consumers' purchase desire and personal health. The traditional detection means, relied mainly on artificial lighting detection, are affected by many human factors. In this paper, multiple image processing algorithms were adopted for obtaining the egg yolk and air cell characteristics which are closely related to the freshness degree of eggs. The ratio of egg yolk to whole egg area and the ratio of air cell to whole egg area are selected as characteristic values to establish a real-time discriminant model with the actual haugh unit values through experiments. The determination coefficient and the average error of the model for predicting freshness of eggs were 0.96435 and 8.39%, respectively,, indicating that the image processing is an effective method to identify the freshness degree of eggs.
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