为快速准确地提取地面三维激光扫描仪获取林分点云中的单株树木点云,提出一种基于密度的抗噪空间聚类(Density-Based Spatial Clustering of Application with Noise,DBSCAN)的树木分割算法。首先采用高斯滤波对林分点云去噪,在林分点...为快速准确地提取地面三维激光扫描仪获取林分点云中的单株树木点云,提出一种基于密度的抗噪空间聚类(Density-Based Spatial Clustering of Application with Noise,DBSCAN)的树木分割算法。首先采用高斯滤波对林分点云去噪,在林分点云归一化的基础上对林分点云垂直分段,然后采用DBSCAN算法垂直分段聚类,再计算每个垂直分段中每个簇的中心点,根据簇中心点间的距离判定簇间的相邻关系,并由此匹配树干段点云,最后采用RANSAC(Random Sample Consensus)算法对树干段点云拟合直线,并根据点与拟合直线间的距离判定点的归属以实现树木分割。在郁闭度分别为中与高的林分中,所提算法的调和值F范围分别为0.88~0.99与0.72~0.74,基于距离判别的树木分割算法的F范围分别为0.84~0.90与0.73~0.79。所提算法在不同郁闭度的林分点云中均能有效分割单株树木点云,特别是在郁闭度为中的林分中有较好表现,可实现对林分点云的精确树木分割。展开更多
The formation of reversed micelle of primary amine N1923 in different solvents is firstly investigated by determining the interfacial tension and electric conductivity in the organic phase and the IR spectra. A signif...The formation of reversed micelle of primary amine N1923 in different solvents is firstly investigated by determining the interfacial tension and electric conductivity in the organic phase and the IR spectra. A significant difference has been discovered for the formation of reversed micelle between the sulfate and the chloride.展开更多
文摘为快速准确地提取地面三维激光扫描仪获取林分点云中的单株树木点云,提出一种基于密度的抗噪空间聚类(Density-Based Spatial Clustering of Application with Noise,DBSCAN)的树木分割算法。首先采用高斯滤波对林分点云去噪,在林分点云归一化的基础上对林分点云垂直分段,然后采用DBSCAN算法垂直分段聚类,再计算每个垂直分段中每个簇的中心点,根据簇中心点间的距离判定簇间的相邻关系,并由此匹配树干段点云,最后采用RANSAC(Random Sample Consensus)算法对树干段点云拟合直线,并根据点与拟合直线间的距离判定点的归属以实现树木分割。在郁闭度分别为中与高的林分中,所提算法的调和值F范围分别为0.88~0.99与0.72~0.74,基于距离判别的树木分割算法的F范围分别为0.84~0.90与0.73~0.79。所提算法在不同郁闭度的林分点云中均能有效分割单株树木点云,特别是在郁闭度为中的林分中有较好表现,可实现对林分点云的精确树木分割。
文摘The formation of reversed micelle of primary amine N1923 in different solvents is firstly investigated by determining the interfacial tension and electric conductivity in the organic phase and the IR spectra. A significant difference has been discovered for the formation of reversed micelle between the sulfate and the chloride.