Open AccessApplication of Hyperspectral Images and Spectral Features of Yolks in Egg Freshness Detection
Author(s) -
Shiqi Huang,
Xuewen Pu,
Peng Luo
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1634/1/012123
Subject(s) - hyperspectral imaging , yolk , spectral signature , pattern recognition (psychology) , artificial intelligence , spectrometer , computer science , remote sensing , mathematics , biological system , chemistry , biology , food science , geography , physics , optics
The detection of egg freshness is an important basis and means to obtain the effective value of eggs. In order to more effectively and reasonably classify and monitor the quality of eggs, a new egg quality identification method based on the hyperspectral image data of egg yolk and its spectral characteristics data is proposed. In this method, the spectral and hyperspectral data of the raw yolk and the boiled yolk are obtained by using a spectrometer and a hyperspectral imager, respectively. By analyzing different spectral properties, building a relationship model between each other, combining with different results, the new proposed method has achieved the purpose of identifying the freshness of eggs. The test experiments were carried out with different batches eggs of the same type. The results show that the method proposed in this paper can detect the freshness of eggs, and can provide new ideas and references for egg quality classification and detection.