Leaf surface roughness measure based on shape from focus
Background
Surface roughness has a significant effect on leaf wettability, consequently influencing the efficiency and effectiveness of pesticide spraying application. Therefore, surface roughness measure of plant leaves is conducive to relevant researches. In order to characterize the surface roughness, present methods have to draw support from large apparatus, but they are generally high-cost and not portable enough for field measurement. Methods those instruments even have potentially inherent drawback such as absence of relation between pixel intensity and corresponding height for scanning electron microscope (SEM).
Results
An imaging system with variable object distance is set up to capture images of plant leaves and a shape from focus (SFF) based method is proposed. These space-variantly blurred images are processed with the proposed algorithm to yield surface roughness of plant leaves. The algorithm mainly improves the current SFF method in image alignment, focus distortion correction, and NaN values introducing to make it applicative for precise 3d-reconstruction and surface roughness measure in small scale.
Conclusion
Compared with method via optical three-dimensional interference microscope, the proposed method preserves the overall topography of leaf surface and meanwhile achieves superior cost performance. Experiments on standard gauge blocks revealed the RMSE of step was approximately 4.44μm. Furthermore, the focus measure operator SML was supposed to perform best according to Friedman/Nemenyi test.
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Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.
Posted 05 Jan, 2021
Received 16 Jan, 2021
On 05 Jan, 2021
Invitations sent on 04 Jan, 2021
On 28 Dec, 2020
On 28 Dec, 2020
On 28 Dec, 2020
On 28 Dec, 2020
Leaf surface roughness measure based on shape from focus
Posted 05 Jan, 2021
Received 16 Jan, 2021
On 05 Jan, 2021
Invitations sent on 04 Jan, 2021
On 28 Dec, 2020
On 28 Dec, 2020
On 28 Dec, 2020
On 28 Dec, 2020
Background
Surface roughness has a significant effect on leaf wettability, consequently influencing the efficiency and effectiveness of pesticide spraying application. Therefore, surface roughness measure of plant leaves is conducive to relevant researches. In order to characterize the surface roughness, present methods have to draw support from large apparatus, but they are generally high-cost and not portable enough for field measurement. Methods those instruments even have potentially inherent drawback such as absence of relation between pixel intensity and corresponding height for scanning electron microscope (SEM).
Results
An imaging system with variable object distance is set up to capture images of plant leaves and a shape from focus (SFF) based method is proposed. These space-variantly blurred images are processed with the proposed algorithm to yield surface roughness of plant leaves. The algorithm mainly improves the current SFF method in image alignment, focus distortion correction, and NaN values introducing to make it applicative for precise 3d-reconstruction and surface roughness measure in small scale.
Conclusion
Compared with method via optical three-dimensional interference microscope, the proposed method preserves the overall topography of leaf surface and meanwhile achieves superior cost performance. Experiments on standard gauge blocks revealed the RMSE of step was approximately 4.44μm. Furthermore, the focus measure operator SML was supposed to perform best according to Friedman/Nemenyi test.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.