African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6578

Full Length Research Paper

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

  Tao Zhu and Qiaohua Wang*        
College of Engineering, Huazhong Agricultural University, Wuhan, 430070, P. R. China.
Email: [email protected]

  •  Accepted: 20 October 2010
  •  Published: 31 March 2011



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.


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