Abstract
Aiming at the shortcoming of using a single feature to measure the quality of strawberry in traditional strawberry automatic grading system, we proposed a new method to evaluate the quality of strawberry from the aspects of maturity, mass and shape. Firstly, the H parameters in the HSV color model was calculated and analyzed to determine the maturity of strawberries. Secondly, the mass of strawberry was measured by the image projection area-mass function, and then the K-means clustering method and the discriminant analysis were used to obtain the shape classification of strawberry. Finally, the composite score of strawberry mass and shape might be calculated by weighting method to determine strawberry quality grade. Compared to the manual rating, the results showed that the accuracy rate of this new method was more than 90%.
Publication Date
3-28-2018
First Page
146
Last Page
150
DOI
10.13652/j.issn.1003-5788.2018.03.031
Recommended Citation
Tao, YANG; Yunwei, ZHANG; and Shuang, GOU
(2018)
"Research on strawberry automatic classification based on the machine vision,"
Food and Machinery: Vol. 34:
Iss.
3, Article 31.
DOI: 10.13652/j.issn.1003-5788.2018.03.031
Available at:
https://www.ifoodmm.cn/journal/vol34/iss3/31
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