Cargando…
Plant leaf veins coupling feature representation and measurement method based on DeepLabV3+
The plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ is proposed to solve problems of slow segmentation, partial occlusion of leaf veins, and low measurement accuracy of leaf veins parameters. Firstly, to solve the problem of slow segmentation, the lightwei...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9730334/ https://www.ncbi.nlm.nih.gov/pubmed/36507417 http://dx.doi.org/10.3389/fpls.2022.1043884 |
_version_ | 1784845645283065856 |
---|---|
author | Liu, Xiaobao Xu, Biao Gu, Wenjuan Yin, Yanchao Wang, Hongcheng |
author_facet | Liu, Xiaobao Xu, Biao Gu, Wenjuan Yin, Yanchao Wang, Hongcheng |
author_sort | Liu, Xiaobao |
collection | PubMed |
description | The plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ is proposed to solve problems of slow segmentation, partial occlusion of leaf veins, and low measurement accuracy of leaf veins parameters. Firstly, to solve the problem of slow segmentation, the lightweight MobileNetV2 is selected as the extraction network for DeepLabV3+. On this basis, the Convex Hull-Scan method is applied to repair leaf veins. Subsequently, a refinement algorithm, Floodfill MorphologyEx Medianblur Morphological Skeleton (F-3MS), is proposed, reducing the burr phenomenon of leaf veins’ skeleton lines. Finally, leaf veins’ related parameters are measured. In this study, mean intersection over union (MIoU) and mean pixel accuracy (mPA) reach 81.50% and 92.89%, respectively, and the average segmentation speed reaches 9.81 frames per second. Furthermore, the network model parameters are compressed by 89.375%, down to 5.813M. Meanwhile, leaf veins’ length and width are measured, yielding an accuracy of 96.3642% and 96.1358%, respectively. |
format | Online Article Text |
id | pubmed-9730334 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97303342022-12-09 Plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ Liu, Xiaobao Xu, Biao Gu, Wenjuan Yin, Yanchao Wang, Hongcheng Front Plant Sci Plant Science The plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ is proposed to solve problems of slow segmentation, partial occlusion of leaf veins, and low measurement accuracy of leaf veins parameters. Firstly, to solve the problem of slow segmentation, the lightweight MobileNetV2 is selected as the extraction network for DeepLabV3+. On this basis, the Convex Hull-Scan method is applied to repair leaf veins. Subsequently, a refinement algorithm, Floodfill MorphologyEx Medianblur Morphological Skeleton (F-3MS), is proposed, reducing the burr phenomenon of leaf veins’ skeleton lines. Finally, leaf veins’ related parameters are measured. In this study, mean intersection over union (MIoU) and mean pixel accuracy (mPA) reach 81.50% and 92.89%, respectively, and the average segmentation speed reaches 9.81 frames per second. Furthermore, the network model parameters are compressed by 89.375%, down to 5.813M. Meanwhile, leaf veins’ length and width are measured, yielding an accuracy of 96.3642% and 96.1358%, respectively. Frontiers Media S.A. 2022-11-24 /pmc/articles/PMC9730334/ /pubmed/36507417 http://dx.doi.org/10.3389/fpls.2022.1043884 Text en Copyright © 2022 Liu, Xu, Gu, Yin and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Liu, Xiaobao Xu, Biao Gu, Wenjuan Yin, Yanchao Wang, Hongcheng Plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ |
title | Plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ |
title_full | Plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ |
title_fullStr | Plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ |
title_full_unstemmed | Plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ |
title_short | Plant leaf veins coupling feature representation and measurement method based on DeepLabV3+ |
title_sort | plant leaf veins coupling feature representation and measurement method based on deeplabv3+ |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9730334/ https://www.ncbi.nlm.nih.gov/pubmed/36507417 http://dx.doi.org/10.3389/fpls.2022.1043884 |
work_keys_str_mv | AT liuxiaobao plantleafveinscouplingfeaturerepresentationandmeasurementmethodbasedondeeplabv3 AT xubiao plantleafveinscouplingfeaturerepresentationandmeasurementmethodbasedondeeplabv3 AT guwenjuan plantleafveinscouplingfeaturerepresentationandmeasurementmethodbasedondeeplabv3 AT yinyanchao plantleafveinscouplingfeaturerepresentationandmeasurementmethodbasedondeeplabv3 AT wanghongcheng plantleafveinscouplingfeaturerepresentationandmeasurementmethodbasedondeeplabv3 |