摘要
叶子是植物最重要的器官之一,建立植物叶片的高精度曲面模型对于开展植物叶片形态特征分析和冠层光分布计算等研究具有重要意义。该文提出了一种基于点云数据的植物叶片曲面重构方法,该方法首先对原始点云数据进行噪声点剔除和数据精简,然后采用Delaunay三角剖分方法生成初始网格曲面,再对网格曲面进行优化处理。结果表明该方法能够基于激光扫描三维点云数据快速重构出植物叶片的高精度网格曲面,包括萎蔫和枯萎等复杂形态。该研究可为植物建模与可视化相关研究提供参考。
As one of the most important organs,the high-accuracy plant leaf geometric model contributes to agronomic research such as shape feature exaction and canopy light distribution calculation.This paper proposed a method of surface reconstruction based on 3D scanned point cloud for plant leaves.This method generated the initial surface mesh from the point cloud through Delaunay triangulation after removing the noise points,and an optimization algorithm was applied to eliminate wrong edges.The results show that the proposed method can reconstruct high-quality 3D surface of plant leaf from point cloud data,which is also applicable to complex shapes like wilting and withered leaves.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2012年第3期184-190,共7页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家自然科学基金项目(61003188)
北京市优秀人才培养资助项目(2010D002020000005)
北京市农林科学院科技创新能力建设专项(KJCX201104011)资助
关键词
植物
重建
模型
最小二乘平面
网格
点云
plants
reconstruction
models
least squares approximations
mesh generation
point cloud
