Three-dimensional(3D)parametric measurements of individual gravels in the Gobi region using point cloud technique

Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.

A modified method of discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces

This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by normal tensor voting theory,(2)co ntraction of trace feature points,(3)connection of trace feature points,(4)linearization of trace segments,and(5)connection of trace segments.A sensitivity analysis was then conducted to identify the optimal parameters of the proposed method.Three field cases,a natural rock mass outcrop and two excavated rock tunnel surfaces,were analyzed using the proposed method to evaluate its validity and efficiency.The results show that the proposed method is more efficient and accurate than the traditional trace mapping method,and the efficiency enhancement is more robust as the number of feature points increases.

Landslide data mosaicking based on an airborne laser point cloud and multi-beam sonar images

Landslides are one of the most disastrous geological hazards in southwestern China.Once a landslide becomes unstable,it threatens the lives and safety of local residents.However,empirical studies on landslides have predominantly focused on landslides that occur on land.To this end,we aim to investigate ashore and underwater landslide data synchronously.This study proposes an optimized mosaicking method for ashore and underwater landslide data.This method fuses an airborne laser point cloud with multi-beam depth sounder images.Owing to their relatively high efficiency and large coverage area,airborne laser measurement systems are suitable for emergency investigations of landslides.Based on the airborne laser point cloud,the traversal of the point with the lowest elevation value in the point set can be used to perform rapid extraction of the crude channel boundaries.Further meticulous extraction of the channel boundaries is then implemented using the probability mean value optimization method.In addition,synthesis of the integrated ashore and underwater landslide data angle is realized using the spatial guide line between the channel boundaries and the underwater multibeam sonar images.A landslide located on the right bank of the middle reaches of the Yalong River is selected as a case study to demonstrate that the proposed method has higher precision thantraditional methods.The experimental results show that the mosaicking method in this study can meet the basic needs of landslide modeling and provide a basis for qualitative and quantitative analysis and stability prediction of landslides.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.

A state-of-the-art review of automated extraction of rock mass discontinuity characteristics using three-dimensional surface models

In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.

An unmanned ground vehicle phenotyping-based method to generate three-dimensional multispectral point clouds for deciphering spatial heterogeneity in plant traits

Fusing three-dimensional(3D)and multispectral(MS)imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge.Acquiring high-quality 3D MS point clouds(3DMPCs)of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with a complex canopy structure.Here,we present a novel 3D spatial–spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view planning for adaptive data acquisition and neural reference field(NeREF)for radiometric calibration.This approach was used to acquire 3DMPCs of perilla,tomato,and rapeseed plants with diverse plant architecture and leaf morphological features evaluated by the accuracy of chlorophyll content and equivalent water thickness(EWT)estimation.The results showed that the completeness of plant point clouds collected by this approach was improved by an average of 23.6%compared with the fixed viewpoints alone.The NeREF-based radiometric calibration with the hemispherical reference outperformed the conventional calibration method by reducing the root mean square error(RMSE)of 58.93%for extracted reflectance spectra.The RMSE for chlorophyll content and EWT predictions decreased by 21.25%and 14.13%using partial least squares regression with the generated 3DMPCs.Collectively,our study provides an effective and efficient way to collect high-quality 3DMPCs of plants under natural light conditions,which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits,and thus will facilitate plant biology and genetic studies as well as crop breeding.

Three-dimensional face point cloud hole-filling algorithm based on binocular stereo matching and a B-spline

When obtaining three-dimensional(3D)face point cloud data based on structured light,factors related to the environment,occlusion,and illumination intensity lead to holes in the collected data,which affect subsequent recognition.In this study,we propose a hole-filling method based on stereo-matching technology combined with a B-spline.The algorithm uses phase information acquired during raster projection to locate holes in the point cloud,simultaneously extracting boundary point cloud sets.By registering the face point cloud data using the stereo-matching algorithm and the data collected using the raster projection method,some supplementary information points can be obtained at the holes.The shape of the B-spline curve can then be roughly described by a few key points,and the control points are put into the hole area as key points for iterative calculation of surface reconstruction.Simulations using smooth ceramic cups and human face models showed that our model can accurately reproduce details and accurately restore complex shapes on the test surfaces.Simulation results indicated the robustness of the method,which is able to fill holes on complex areas such as the inner side of the nose without a prior model.This approach also effectively supplements the hole information,and the patched point cloud is closer to the original data.This method could be used across a wide range of applications requiring accurate facial recognition.

基于法线微分的3维声呐点云自适应简化方法

在不损失原始点云数据质量的前提下,大幅约简点云数据量是减少存储空间、降低后期计算强度的重要预处理步骤。针对这一需求,提出了针对水下3维声呐点云数据的自适应简化方法。首先,定义法线微分算子来识别点云中几何尺度的骤变,从而实现原始点云中边界部分点云和主体部分点云的分割。其次,对于点云的边界部分,应用移动最小二乘法来对边界点进行优化,降低噪点的影响,并保持其曲面的几何一致性;基于体素栅格结构,在边界上使用八叉树进行降采样,并在此基础上实施局部最远点采样,在实现均匀简化的同时保证已简化点云的边界部分具有各向同性,有效保留边界部分点云的几何特征信息。再次,对于点云的主体部分,为保持简化后点云整体的各向同性,使用体素中心采样法来减少数据量。然后,通过高斯滤波平滑点云表面,最后,整合简化后的边界点云和主体点云,得到简化结果。实验结果表明,提出的简化方法计算成本低、处理速度快,在与现行典型算法保持一致简化率的情况下,对水下点云数据的简化速度提高了约32%。另外,通过表面密度对比与几何失真分析,证明了提出方法对水下3维点云边界点及整体分布的优化作用。综上,此方法能提高水下作业目标探测效率,得到保留重要几何特征信息并具有各向同性的水下任务目标点云简化结果。

水下声呐惯性系统定位研究

为应对传统声呐惯性系统在弱纹理水下环境中定位精度较低的问题,提出将声呐惯性滤波里程计应用于水下声呐惯性系统定位。依据声呐成像原理对声呐图像进行特征提取,运用迭代最近点算法(ICP)进行特征匹配。通过将点云匹配结果与IMU数据融合,提升状态估计的稳定性。这种方法使用IMU数据进行状态预测,并以声呐ICP匹配结果作为观测进行状态更新。最后将该滤波里程计与ICP顺序匹配结果一起纳入图优化框架进行位姿优化。试验表明,相比于传统方法,该方法的定位精度更高,能适应弱纹理环境。

基于特征点匹配的排水管道声点云模型配准算法

三维重建技术逐渐成为获取全面、完备、准确的排水管道信息的关键手段;而实际检测受到管道堵塞等工况与管道检测规程等因素限制,造成所获得的管道声呐点云模型会出现位姿不同、部分重叠或空缺等情况,需要通过配准获取完整管道模型;同时,传统ICP算法针对管道模型存在效率低、精度差的问题;因此,文章提出基于特征点匹配的粗配准与改进的ICP精细配准相结合的点云配准算法;首先,利用ISS特征点检测法检测出模型特征点,通过FPFH对特征点进行进一步的描述;其次,采用RANSAC算法筛选出正确特征匹配点集,利用四元数法解算出初始变换参数完成粗配准;最后,在粗配准基础上,通过改进最近对应点查询的ICP算法完成精细配准;实验结果表明了该文算法的可行性与优越性,能为后续排水管道缺陷检测提供高完备、全面、准确的点云模型。

基于最近点迭代的水下三维声图增强算法

由于复杂的水下环境和声呐硬件的限制,三维成像声呐(3DIS)图像质量较差,表现为图像目标表面点的稀疏和缺失。为了提高图像质量,我们提出了一种基于配准和融合的目标增强方法。迭代最邻近点(ICP)算法是经典的点云配准算法,是一种用于配准2个或多个点云数据集的迭代优化方法。ICP方法可直接用于点云数据,具有实施简单、迭代速度快的优点。该算法通过对齐和融合的方法叠加多帧点云来增强点云,可以改善目标点云稀疏和缺失的问题。实验结果表明,我们提出的增强方法能有效增强声呐图像,提高三维声呐图像的质量和可理解性。

基于三维声纳点云的水下沉井地形探测技术

为了解决水下沉井地形监测难题,给出了一种基于三维扫描声纳的地形监测方法以及地形点云的高精度快速处理方法。首先,结合沉井特点,给出了一种悬挂式三维扫描声纳扫描沉井水下地形方法;然后,结合沉井形状及点云特点,给出由降采样点云抽稀法、基于欧式距离的区域自生长算法的点云去噪方法和基于K-means++聚类算法的沉井水下地形分割方法等组成的水下地形点云处理方法,实现了基于声纳点云的地形点云快速获取及水下地形恢复。实验结果表明,该方法可有效用于沉井水下地形探测。

三维声呐在水下沉船姿态探测中的应用

研究采用多波束测深声呐与三维扫描声呐相结合,获取水下沉船姿态数据及附近海底地形点云数据的方法。通过实例阐述数据采集、数据处理过程的关键因素,并采用环境光遮蔽算法对点云数据进行了可视化渲染。结果表明,该种方式点云数据完整、沉船细节清晰,可为沉船清理作业中的风险评估和决策制定提供关键的技术支持。

基于Ransac算法的多波束点云人工鱼礁提取方法

投放人工鱼礁作为海洋牧场建设的重要环节,其投放质量评估工作日益受到重视。为实现大范围的人工鱼礁三维信息的自动识别与提取,提升人工鱼礁量化评估的质量,提出了一种基于Ransac算法的多波束点云人工鱼礁提取方法。该方法首先利用多波束声呐获取点云,在对点云进行分割、去噪等预处理后,利用Ransac算法将点云分为内外点集,内点集近似拟合为海底平面,外点集为人工鱼礁。在浙江嵊泗马鞍列岛某礁区进行了相关试验,实现了整体和单体鱼礁的提取,提取正确度达94.79%,完整度达91%,能够较好地提取鱼礁的三维形态、位置、尺寸、高度、空方等信息。研究表明,本方法可以大范围地应用于各型人工鱼礁目标投放效果的量化评估。

基于阈值自适应确定的多波束点云滤波算法

针对水下多波束地形测量点云去噪问题,提出了一种基于阈值自适应确定的点云滤波算法。首先引入虚拟网格对多波束点云进行分区编号,并采用二次分层统计法剔除显著离群噪点;其次归一化计算网格内种子点与邻域各点的坡度角,引入k-Medoids聚类算法自适应更新坡度阈值;最后按照多尺度滤波窗口逐级对点云进行迭代运算,得到精细化地形点云。2个实验区的多波束点云滤波实验结果表明,本文算法能较好去除多波束点云的噪声和非地形点,有效提高坡度阈值的自适应性,滤波精度有明显提升,可以适用于大规模的多波束点自动化云滤波工作。

基于局部异常因子算法的三维声纳单帧重建研究

海洋环境的复杂性会使三维声纳获取到的点云中存在异常点,从而影响点云的后期处理和可视化。将获取到的声纳数据依次进行三维波束成像、最大值滤波和坐标系转换,进而得到原始点云。提出将局部异常因子(LOF)算法应用到点云去噪、剔除干扰的异常点,并用一种改进三角网生长方法进行单帧重建。改进三角网生长法简化了三角网生成中关键的“第三点”搜寻过程,通过实际数据处理分析得知:相比于传统阈值去噪方式,基于LOF算法的去噪方式能够在保持目标真实轮廓的前提下有效剔除非目标点;经过所提去噪方式的声纳数据能够得到更贴合实际目标轮廓的三维重建结果。

水工建筑物水下三维检测精确定位分析

在复杂海况下,对水下的水工建筑物进行三维检测精确定位分析,目前有多种设备可选择。但检测的可靠性和精度需要进一步分析和验证。为此,结合广东揭阳石化原油码头工程,采用多波束测深仪系统和水下三维实时3D声呐系统,以点云数据建模,将2种系统采集的数据融合处理,可对建筑物的坐标和高程进行精确分析。其中,多波束测深仪系统可用于水下建筑物绝对坐标的测量,而实时3D声呐系统可取得目标物精确的模型图像,2种数据融合处理后,即可用可视化的方法对目标物的位置和状态进行准确分析。该方法可用于港口和码头维护以及水下建筑物检测,为老码头的改造、修复提出有效的检测定位方法和可视工具。

基于全向声呐的引水隧洞点云模型去噪方法研究

三维重建技术逐渐成为引水隧洞运营期安全检测的关键手段;而受隧洞特殊水文环境噪声、数据采集设备噪声以及载体运动噪声等影响,采集的点云数据不可避免的会遭受到噪声干扰,导致有用信息缺乏,不利于三维重建的进行;因此,文章提出了基于声呐数据特征点的点云去噪算法,实现隧洞点云数据的去噪;首先,该文依据引水隧洞声呐点云数据的特点,定义视觉距离和视角向量特征参数;其次,通过耦合视角向量与点云法向量估计点云漂移向量,并使用核函数方法估计视角距离参数的概率密度分布从而计算漂移距离;最后,采用漂移算法在保持点云模型特征的同时实现噪声的滤波;实验结果表明,文章提出的算法在去除隧洞点云模型数据噪声的同时能很好的保持引水隧洞模型的细节特征,为后续隧洞病害的检测提供高精度点云数据模型。

基于快速双边滤波法的三维成像声呐在海底管道检测中的应用

文章以三维实时声呐(Echoscope C500)为例,经过对其获取的实时数据进行一种基于数字图像噪声处理的快速双边滤波法处理后,使三维声呐数据提供目标更精确的姿态信息。通过同一位置上浅地层剖面仪和三维声呐各自数据的对比,说明三维声呐相较于传统测量设备的优势,可以作为水下管道测量的一种技术支持。

影响三维声纳成像质量的因素分析及应用

三维成像声纳系统具有高分辨率、全方位成图的特点,正在成为水下工程精细测量的重要技术手段。根据成像原理的不同,将三维成像声纳系统划分三类,分别阐述其工作原理,针对影响三维成像声纳测量精度和分辨率的因素展开分析,并提出了测量时相应的应对措施。通过在海上风电桩基测量项目中的应用,验证了给出的提高测量成果质量措施的有效性以及三维成像声纳系统在水下工程精细测量中的优势。