Non-destructive detection of Sudan dye duck eggs based on computer vision and fuzzy cluster analysis

Authors

  • Tao Zhu Author

Keywords:

Duck egg, Sudan dye, computer vision,, fuzzy cluster analysis, non-destructive detection.

Abstract

A method of non-destructive detection of Sudan dye duck eggs was developed using image processing 
and fuzzy cluster analysis. Duck egg color images were obtained by using a computer vision device. 
Through the component analysis of RGB image, it was found that the yolk region could be viewed 
distinctly in the gray scale image of B-component, and this characteristic was used to separate the yolk 
region from the white region. By extracting and comparing the color parameters, the R-component 
values of the yolk region showed obvious differences for Sudan dye and natural red-yolk duck eggs. A 
fuzzy discriminant model for the detection of Sudan dye duck eggs was established using the yolk’s 
color parameters. The experimental results indicated that this model had good capability of 
identification for Sudan dye eggs. 

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Published

2019-10-04

How to Cite

Non-destructive detection of Sudan dye duck eggs based on computer vision and fuzzy cluster analysis. (2019). Frontiers of Agriculture and Food Technology, 9(1), 71-75. https://kevinpage.org/index.php/FAFT/article/view/764

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