Abstract
In this paper, an online detection platform for jujube surface defects based on machine vision is designed to realize the automatic real-time measurement of full-surface information of jujubes. According to the characteristics of jujubes and their surface defects, the blob analysis algorithm in the color space was used to separate the jujubes from the background and identification of the surface defects of jujube model was proposed. The color space model and the segmentation threshold of different defect characteristics were given,the broken fruit, mold fruit, pulp head fruit, insect fruit and other typical jujubes surface defects identification was realized speedily and accurately . It shows that the results of this study are robust and reliable in this experiment, and the accuracy of defective identification is over 90%.
Publication Date
1-28-2018
First Page
126
Last Page
129
DOI
10.13652/j.issn.1003-5788.2018.01.025
Recommended Citation
Chao, HAI; Fengxia, ZHAO; and Shuo, SUN
(2018)
"Research on online detection for jujube surface defects based on blob analysis,"
Food and Machinery: Vol. 34:
Iss.
1, Article 25.
DOI: 10.13652/j.issn.1003-5788.2018.01.025
Available at:
https://www.ifoodmm.cn/journal/vol34/iss1/25
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