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首页> 外文期刊>African Journal of Agricultural Research >Non-destructive detection of Sudan dye duck eggs based on computer vision and fuzzy cluster analysis
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Non-destructive detection of Sudan dye duck eggs based on computer vision and fuzzy cluster analysis

机译:基于计算机视觉和模糊聚类分析的苏丹红鸭蛋无损检测

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摘要

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.
机译:通过图像处理和模糊聚类分析,开发了一种苏丹红鸭蛋的无损检测方法。鸭蛋彩色图像通过使用计算机视觉设备获得。通过对RGB图像的成分分析,发现在B成分的灰度图像中可以清晰地看到卵黄区域,并且此特征用于将卵黄区域与白色区域分开。通过提取和比较颜色参数,蛋黄区域的R成分值对于苏丹红和天然红蛋鸭蛋显示出明显的差异。利用蛋黄的颜色参数,建立了用于检测苏丹红染色鸭蛋的模糊判别模型。实验结果表明,该模型具有良好的苏丹红鸡蛋识别能力。

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