Separating clods and stones from potato tubers based on color and shape

  • Jinfeng Geng
  • Linfang Xiao
  • Yingwang Gao
  • Xiuqin RaoEmail author
Original Paper


The separation of clods and stones from the harvested potato tuber has always been a prevalent problem in the world. However, the precision of sorting was restricted by the potato tubers covered with mud on the surface. This paper studied methods of separating clods and stones from potato tubers based on shape and color. An image acquisition system consisted of a light source, a camera, a computer was built for this experiment. The color features were extracted from the components of RGB and HSV images by the two-dimensional Haar Wavelet Transform and put into SVM (support vector machine) to classify the object after principal component analysis. The shape features which contained the original contour and corrected contour described by the mathematical statistical methods was extracted and used for separation by SVM. The experimental result showed that it was effective to separate clods and stones from potato tubers based on the extracted color and shape features, respectively. The combination of color and shape features could increase the accuracy rate of classification, especially for potato tubers and clods. The overall accuracy rate was 97.8% in 2016 and 98.1% in 2017. It was evident that the color features dominate in the classification model. Shape features based on the correcting image showed positive effect in classification. It turned out that the combination of shape and color features can obviously improve classification performance.


Machine vision Potato tuber Color feature Shape feature Foreign material Separation 



The authors gratefully acknowledge the financial support of National key R&D plan “intelligent agricultural equipment” of China (Grant No. 2016YFD0701600). We all appreciate the experimental equipment support provided by Key Laboratory of on Site Processing Equipment for Agricultural Products, Ministry of Agriculture, P.R. China.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human or animal subjects.

Informed consent

Not applicable.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Jinfeng Geng
    • 1
    • 2
  • Linfang Xiao
    • 1
    • 2
  • Yingwang Gao
    • 1
    • 2
  • Xiuqin Rao
    • 1
    • 2
    Email author
  1. 1.College of Biosystems Engineering and Food ScienceZhejiang UniversityHangzhouPeople’s Republic of China
  2. 2.Key Laboratory of On Site Processing Equipment for Agricultural ProductsMinistry of AgricultureHangzhouPeople’s Republic of China

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