Multi-view 3D reconstruction of seedling using 2D image contour
文献类型: 外文期刊
第一作者: Chen, Qingguang
作者: Chen, Qingguang;Huang, Shentao;Liu, Shuang;Zhong, Mingwei;Zhang, Guohao;Song, Liang;Zhang, Xinghao;Zhang, Jingcheng;Wu, Kaihua;Ye, Ziran;Kong, Dedong
作者机构:
关键词: RGB-D camera; rotation axis optimisation; Projected contour constraint; Point cloud; Phenotypic measurement
期刊名称:BIOSYSTEMS ENGINEERING ( 影响因子:4.4; 五年影响因子:5.2 )
ISSN: 1537-5110
年卷期: 2024 年 243 卷
页码:
收录情况: SCI
摘要: 3D reconstruction of seedling can provide comprehensive and quantitative spatial structure information, offering an effective digital tool for breeding research. However, accurate and efficient reconstruction of seedling is still a challenging work due to limited performance of depth sensor for seedling with small -size stem and unavoidable error for multi -view point cloud registration. Therefore, in this paper, we propose an accurate multi -view 3D reconstruction method for seedling using 2D image contour to constrain 3D point cloud. The rotation axis is calibrated and optimised by minimising point -to -contour distance between 2D image contour and projected exterior points from 3D point cloud. Then, to remove outliers and noise, we introduce the seedling mask of 2D image to constrained and delete projected outlier points of 3D model from corresponding view. Furthermore, we propose a residual -guided method to recognise missing region for 3D model and complete 3D model of small -size stem. Finally, we can obtain an accurate 3D model of seedling. The reconstruction accuracy is evaluated by average distance between projected contour of 3D model and 2D image contour of all views (0.3185 mm). Then, the phenotypic parameters were calculated from 3D model and the results are close to manual measurements (Plant height: R 2 = 0.98, RMSE = 2.3 mm, rRMSE =1.52%; Petioles inclination angle: R 2 = 0.99, RMSE = 0.73 degrees , rRMSE = 1.41%; Leaf area: R 2 = 0.66, RMSE = 1.05 cm 2 , rRMSE = 7.63%; Leaf inclination angle: R 2 = 0.99, RMSE = 1.01 degrees , rRMSE = 1.72%; Stem diameter: R 2 = 0.95, RMSE = 0.12 mm, rRMSE = 5.43%). Breeders can improve the selection of more resilient varieties and cultivars to different growing conditions starting from the dynamic analysis of their phenotype.
分类号:
- 相关文献
作者其他论文 更多>>
-
Yield prediction through UAV-based multispectral imaging and deep learning in rice breeding trials
作者:Zhou, Hongkui;Lou, Weidong;Gu, Qing;Ye, Ziran;Hu, Hao;Zhang, Xiaobin;Huang, Fudeng
关键词:UAV; Yield prediction; Multispectral imaging; Deep learning; Rice breeding
-
YOLOv8-LSW: A Lightweight Bitter Melon Leaf Disease Detection Model
作者:Liu, Shuang;Xu, Haobin;Deng, Ying;Cai, Yixin;Wu, Yongjie;Zhong, Xiaohao;Chen, Jianqing;Li, Huiying;Zhong, Fenglin;Zheng, Jingyuan;Lin, Zhiqiang;Zhang, Fengxiang;Ruan, Miaohong
关键词:bitter melon; leaf disease; disease detection; deep learning; YOLO-LSW
-
Rhizosphere-triggered viral lysogeny mediates microbial metabolic reprogramming to enhance arsenic oxidation
作者:Song, Xinwei;Wang, Yiling;Zhao, Kankan;Tang, Xianjin;Xu, Jianming;Ma, Bin;Song, Xinwei;Wang, Yiling;Zhao, Kankan;Ma, Bin;Song, Xinwei;Wang, Yiling;Wang, Youjing;Zhao, Kankan;Tong, Di;Tang, Xianjin;Xu, Jianming;Ma, Bin;Wang, Youjing;Tong, Di;Gao, Ruichuan;Li, Fangbai;Lv, Xiaofei;Kong, Dedong;Ruan, Yunjie;Ruan, Yunjie;Wang, Mengcen;Luo, Yongming;Zhu, Yongguan
关键词:
-
Metagenomics reveal the mechanisms of integrated heterotrophic and sulfur autotrophic denitrification (HSAD) using PBAT/starch as carbon source
作者:Deng, Yale;Li, Junchi;Hu, Yiming;Ruan, Yunjie;Li, Junchi;Hu, Yiming;Chen, Guangsuo;Ruan, Yunjie;Deng, Yale;Taherzadeh, Mohammad J.;Lu, Huifeng;Kong, Dedong;Ma, Bin
关键词:Heterotrophic sulfur autotrophic denitrification; Salinity; Metagenomics; Metatranscriptomics; Functional genes
-
Structural evaluation and formation regularities of garlic clove-like meat in prefabricated grass carp
作者:Yang, Qin;Xie, Junhong;Zhang, Yuting;Tian, Yiling;Liu, Ru;Rong, Jianhua;Xiong, Shanbai;Hu, Yang;Song, Liang;Zhao, Yongqiang;Xiong, Jian
关键词:Prefabricated grass carp; Garlic clove-like meat; Muscle fibers; Texture; Proteomic
-
Navigation line detection algorithm for corn spraying robot based on improved LT-YOLOv10s
作者:Diao, Zhihua;Ma, Shushuai;Li, Xingyi;Zhao, Suna;He, Yan;Li, Jiangbo;Zhang, Jingcheng;Zhang, Baohua;Jiang, Liying;Jiang, Liying
关键词:Deep learning; Corn spraying robot; Navigation line detection; Lightweight network
-
Theaflavins Are Improved by the Oxidation of Catechins in Tannase Treatment During Black Tea Fermentation
作者:Yang, Lijuan;Zhang, Mengxue;Wang, Weiwei;Ye, Shuixin;Jiang, Heyuan;Huang, Jigang;Chen, Yan;Liu, Shuang;Liu, Jiaxin;Ye, Shuixin
关键词:exogenous tannase; black tea; catechins; theaflavins; oxidation mechanism