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Journals
International Journal on Smart Sensing and Intelligent Systems
Volume 12 (2019): Issue 1 (January 2019)
Open Access
Image processing approach for grading tobacco leaf based on color and quality
Agus Harjoko
Agus Harjoko
,
Adhi Prahara
Adhi Prahara
,
Tri Wahyu Supardi
Tri Wahyu Supardi
,
Ika Candradewi
Ika Candradewi
,
Reza Pulungan
Reza Pulungan
and
Sri Hartati
Sri Hartati
| Dec 16, 2019
International Journal on Smart Sensing and Intelligent Systems
Volume 12 (2019): Issue 1 (January 2019)
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Article Category:
research-article
Published Online:
Dec 16, 2019
Page range:
1 - 10
Received:
Jan 30, 2019
DOI:
https://doi.org/10.21307/ijssis-2019-010
Keywords
Tobacco leaf
,
Grading system
,
Image processing
,
Color
,
Quality
© 2019 Agus Harjoko et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Figure 1.
Illustration of tobacco cultivation (FAO, 2018a).
Figure 2.
Tobacco leaf categories based on leaf position.
Figure 3.
Leaf defect categories based on holes or torn positions.
Figure 4.
Mature/ripe leaf subcategories based on the color of tobacco leaf.
Figure 5.
The procedure of leaf area segmentation.
Figure 6.
Area of leaf defects category.
Figure 7.
Small patches applied on the leaf area.
Figure 8.
A set of the threshold to determine the color category.
Figure 9.
A set of the threshold to determine the class in each color category.
Figure 10.
The threshold of hue pixel to segment leaf area.
Figure 11.
The result of a tobacco leaf area segmentation.
Figure 12.
The result of leaf defects detection.
Figure 13.
The distribution of hue-value features of a color-based tobacco leaf category.
Figure 14.
The result of color-based tobacco leaf classification.
The threshold for local color-based classification.
Threshold
Hue
Value
Lower
15
60
Middle
34
127
Upper
80
200
Performance evaluation of color-based tobacco leaf classification.
Actual
M
K
B
M
33
1
2
Predicted
K
8
72
4
B
2
0
82
Accuracy
0.91667
Precision
0.91667
Sensitivity
0.89519
Specificity
0.95751