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基于计算机视觉的三七主根质量的分级方法
() 2016, 42(6):682–685. DOI:10.13331/ki.jhau.2016.06.018
Journal of Hunan Agricultural University (Natural Sciences)
基于计算机视觉的三七主根质量的分级方法
a a* a a b
( a.b. 650500)
摘 要110
2
R2 0.984 9 0.986 6
0.334 8 g 0.494 9 g
关 键 词
中图分类号TN911.73 文献标志码A 文章编号10071032(2016)06068204
Quality classification method of Panax notoginseng taproot
based on computer vision
a a* a a b
Yu Jiayang , Wang Fenghua , Zhang Zhaoguo , Yang Wei , Zhu Hailong
(a.Faculty of Modern Agricultural Engineering; b.Engineering Training Center,Kunming University of Science and
Technology, Kunming ,650500)
Abstract: In this study, 110 dried Panax notoginseng were selected as the test samples. Computer vision technology was
used to obtain the images of Panax notoginseng taproot, which were deal with gray, binary and morphological to extract
the length, width and projection area was ed after preprocess.The prediction models were built to calculate the projection
area and the weight for cone Panax notoginseng and nodule Panax notoginseng, respectively. The results showed that the
weight of mainroot was linely correlated with the projection area. The determination coefficients of cone Panax
notoginseng and nodule Panax notoginseng were 0.984 9 and 0.986 6, respectively. The quality prediction model was
verified by 10-fold cross-validation method. The average error was 0.3348 g and 0.494 9 g for cone Panax notoginseng
and nodule Panax notoginseng, respectively.
Keywords: Panax notoginseng taproot; qu
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