Detection of the Chinese Jujube surface defects by machine vision
CSTR:
Author:
Affiliation:

(Department of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xian, Shaanxi 710021, China)

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Based on LingWu jujube as experimental object, used the Halcon12.0 visual processing software by the method of support vector machine (SVM) in IHS color space to extract the mean value and mean variance of H component as the color eigenvalues. Selected the gaussian kernel function by the experiments. When the kernel parameter was 0.2, and the regular constant was 0.005, the accuracy rate was 94.6%, which greatly improved the efficiency of nondestructive on-line detection, decreased the labor cost and labor intensity, and eliminated the scruple on the accuracy of on-line detection for jujube to processors. It has large research significance in fruit grading.

    Reference
    Related
    Cited by
Get Citation

王春普,文怀兴,王俊杰.基于机器视觉的大枣表面缺陷检测[J].食品与机械英文版,2019,(7):168-171.

Copy
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:May 06,2018
  • Revised:
  • Adopted:
  • Online: November 25,2022
  • Published:
Article QR Code