Journal of System Simulation
Abstract
Abstract: To deal with the classification problems of strawberry in production, a machine vision based strawberry weight and shape grading method was proposed. The strawberry image was segmented by thresholding to extract the fruit. The area and perimeter parameters of the fruit were then calculated and used to build the strawberry weight grading model through regression analysis. Elliptic Fourier descriptor was used to extract the shape features of the fruit, and these shape features were applied to train a support vector machine (SVM) which represented the strawberry shape grading model. 200 samples of strawberries were selected to test both models, and the results showed that the weight grading accuracy was 89.5%, the shape grading accuracy was 96.7%, and the average calculation time were 64 ms and 39 ms, respectively. Therefore, the approaches for grading strawberries were robust and effective.
Recommended Citation
Qing, Zhang; Zou, Xiangjun; Lin, Guichao; and Sun, Yanhui
(2019)
"Image Feature Extraction and Online Grading Method for Weight and Shape of Strawberry,"
Journal of System Simulation: Vol. 31:
Iss.
1, Article 2.
DOI: 10.16182/j.issn1004731x.joss.17-0047
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol31/iss1/2
First Page
7
Revised Date
2017-05-11
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.17-0047
Last Page
9
CLC
TP391.41
Recommended Citation
Zhang Qing, Zou Xiangjun, Lin Guichao, Sun Yanhui. Image Feature Extraction and Online Grading Method for Weight and Shape of Strawberry[J]. Journal of System Simulation, 2019, 31(1): 7-9.
DOI
10.16182/j.issn1004731x.joss.17-0047
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