吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (6): 1811-1817.doi: 10.13229/j.cnki.jdxbgxb201406042

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Online sorting of irregular potatoes based on I-RELIEF and SVM method

ZHANG Bao-hua1, 2, HUANG Wen-qian2, LI Jiang-bo2, ZHAO Chun-jiang1, 2, LIU Cheng-liang1, HUANG Dan-feng1   

  1. 1.State Key Laboratory of Mechanical System and Vibration, Shanghai Jiaotong University, Shanghai 200240, China;
    2.Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China
  • Received:2013-04-26 Online:2014-11-01 Published:2014-11-01

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Abstract: An online sorting method of irregular potatoes is proposed. First, the R-component image is extract, and then the binary image and boundary image are obtained by thresholding method. Second, thirteen essential geometrical features, such as eccentricity, rectangle degree and roundness, and ten Fourier descriptors are extracted. Third, the geometrical features of the potato image sample are feed into the module of I-RELIEF algorithm, which exports a weight for each feature. Fourth, the features of the potato image sample with weights are feed into the training module of Support Vector Machine (SVM). Finally, the classifier model is used to make decision and achieve the grading result online based on the potato's features and weights. Results show that the SVM method can detect and sort four potatoes per second with the help of I-RELIEF module, and the overall accuracy is 98.1%.

Key words: computer vision, potato sorting, fourier descriptor, in-line detection, support vector machine(SVM)

CLC Number: 

  • S126
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