Intelligent extraction of road cracks based on vehicle laser point cloud and panoramic sequence images

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs,this study presents an intelligent strategy for extracting road cracks.This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images.The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously.A convolutional neural network is utilized to extract cracks from the panoramic sequence image.The extracted sequence image is then aligned with the laser point cloud,enabling the assignment of RGB information to the vehicle-mounted three dimensional(3D)point cloud and location information to the two dimensional(2D)panoramic image.Additionally,a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud.The three-dimensional data pertaining to the cracks can be acquired.The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks.The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks.This approach exhibits superior accuracy when compared to conventional methods.Moreover,it facilitates rapid and accurate identification and localization of road cracks,thereby playing a crucial role in ensuring road maintenance and traffic safety.Consequently,this technique finds extensive application in the domains of intelligent transportation and urbanization development.The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

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.

基于知识蒸馏和定位引导的Pointpillars点云检测网络

激光雷达数据由于其几何特性,被广泛应用于三维目标检测任务中。由于点云数据的稀疏性和不规则性,难以实现特征提取的质量和推理速度间的平衡。本文提出一种基于体柱特征编码的三维目标检测算法,以Pointpillars网络为基础,设计Teacher-Student模型框架对回归框尺度进行蒸馏,增加蒸馏损失,优化训练网络模型,提升特征提取的质量。为进一步提高模型检测效果,设计定位引导分类项,增加分类预测和回归预测之间的相关性,提高物体识别准确率。本网络所做改进没有引入额外的网络嵌入。算法在KITTI数据集上的实验结果表明,相比于基准网络,在三维模式下的平均精度值从60.65%提升到了64.69%,鸟瞰图模式下的平均精度值从67.74%提升到70.24%。模型推理速度为45 FPS,在提升检测精度的同时满足了实时性要求。

TREATMENT OF BRONCHIAL ASTHMA WITH CO_2 LASER IRRADIATING POINTS

Therapeutic effect of bronchisl asthma treated With CO2 laser irradiating points was ob-served.Ninety-six cases of bronchial asthma,that were considered cold and insufficiency type accord-ing to TCM,were divided into two groups:one treated with CO2 laser irradiation at Tiantu（CV 22）,Danzhong（CV 17）,Feishu（BL13）and Dingchuan（EX-BI）（n=48）,and the other with warmmoxibustion at same points（n=48）.The symptoms,physical signs and pulmonary ventilation（PEF.VC,FEV1.0,FEV1％and MMEF）were taken as parameter.xhe results showed that thetherapeutic effect In laser irradiation group was better than that in moxibustion group.Moreover,laser irradiation could obviously improve pulmonary ventilation in patients.Therefore,CO2 laser irra-diation is an effective therapy for bronchial asthma.

Laser therapy on points of acupuncture on nerve repair

Paresthesia is the name given to a temporary or permanent sensory loss caused by several surgical procedures that affected the peripheral sensory nerve.In dentistry,common iatrogenic procedures that can lead to sensory loss include third molar removal,

THE TREATMENT OF CERVICAL SPONDYLOPATHY BY LASER ACUPUNCTURE AT THE CERVICAL JIAJI POINTS: AN ANALYSIS OF THERAPEUTIC EFFECT OF 102 CASES

Laser acupuncture therapy was employed in the treatment of spondylopathy.Thetherapeutic effect of the three types of the spondylopathy,nerve root type,vertebral artery type andspinal cord type were stuied and compared.The results indicate a significant difference between thethree types of spondylopathy.The best therapeutic effect was obtained in nerve root type with a remarkable effective rate of 98.5％;the effective rates for the vertebral artery type and the spinal cordtype were 92.3％and 25％,respectively.Combining laser irradiatlon with acupuncture,the therapyposseses the functions of acupuncture,heat effect and mild moxibustion action.Therefore,it showedeffect quickly and had the advantages of short treatment course and high therapeutic effect.Clinicalobservation has confirmed that laser acupuncture is more effective than single laser irradiation.Thistherapy offers another simple but effective method for the treatment of spondylopathy.

Building Facade Point Clouds Segmentation Based on Optimal Dual-Scale Feature Descriptors

To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.

基于改进PointPillars的点云车辆目标检测

针对自动驾驶领域中,激光雷达获取的点云数据存在稀疏性以及边缘噪点误检等问题,提出一种基于改进PointPil-lars的点云车辆目标检测方法。首先,基于SimAM注意力机制改进体素化特征输入,使得网络特征提取阶段能更加关注关键信息,提高特征学习的全局性。其次,基于卷积块注意力模块(CBAM)改进骨干网络结构,提出全新的轻量化通道注意力模块Tiny-CAM和可变形空间注意力模块Deformable-SAM,构建Multi-CBAM骨干网络,提升网络特征提取及特征融合能力。在KITTI数据集以及非公开车库点云数据集上进行验证,实验结果表明,与原网络相比,改进PointPillars方法具有更高的检测精度,平均检测精度提升2.98%,针对遮挡小于30%的点云车辆目标检测精度提升6.51%,证明了该方法的有效性。

Pre-process algorithm for satellite laser ranging data based on curve recognition from points cloud

The satellite laser ranging （SLR） data quality from the COMPASS was analyzed, and the difference between curve recognition in computer vision and pre-process of SLR data finally proposed a new algorithm for SLR was discussed data based on curve recognition from points cloud is proposed. The results obtained by the new algorithm are 85 % （or even higher） consistent with that of the screen displaying method, furthermore, the new method can process SLR data automatically, which makes it possible to be used in the development of the COMPASS navigation system.

移动激光扫描在地铁车站限界测量中的应用

为满足限界要求,地铁车站站台边缘与地铁列车之间存在一定的间隙,但可能发生乘客踏空风险。现需对车站区段的站台边缘至线路中心线距离现状进行快速普查,为更新改造提供决策数据。文章利用移动激光扫描技术快速获取车站段全断面点云,通过点云数据处理提取关键特征点,实现了对空间距离的非接触测量,经传统方法对比复核,验证了该方法的准确性。

改进PointNet++模型在道路杆状物提取中的应用

针对现有道路杆状物提取大多需要针对数据类型人工设计特征、泛用性差、自动化程度低等问题,本文提出一种基于改进PointNet++深度学习网络的道路杆状物语义分割方法,实现了对道路杆状物的提取。首先对原网络模型的感受野、分块大小等参数进行调整,使得该模型更适合道路点云数据;然后针对点云数据不平衡的问题,采用焦点损失函数作为模型的损失函数,使占比较少的类别得到充分训练;最后针对PointNet++网络提取特征时没有考虑邻域内各点特征影响关系的问题,采用邻域特征聚合模块融合邻域信息,提升该网络模型对点云特征的学习能力。为验证所提方法的有效性,使用改进后的网络模型在自建的道路点云组成的数据集上进行了试验,相对于经典PointNet++网络,杆状物类的分割精度明显提升,在简单道路和复杂道路上的交并比(IoU)分别提升了8.44%、15.25%,达到了98.88%、92.50%。

Cloud Detection and Centroid Extraction of Laser Footprint Image of GF-7 Satellite Laser Altimetry

The laser altimeter loaded on the GaoFen-7(GF-7)satellite is designed to record the full waveform data and footprint image,which can obtain high-precision elevation control points for stereo image.The footprint camera equipped on the GF-7 laser altimetry system can capture the energy distribution at the time of laser emission and the image of the ground object where the laser falls,which can be used to judge whether the laser is affected by the cloud.At the same time,the centroid of laser spot on the footprint image can be extracted to monitor the change of laser pointing stability.In this manuscript,a data quality analysis scheme of laser altimetry based on footprint image is presented.Firstly,the cloud detection of footprint image is realized based on deep learning.The fusion result of the model is about 5%better than that of the traditional cloud detection algorithm,which can quickly and accurately determine whether the laser spot is affected by cloud.Secondly,according to the characteristics of footprint image,a threshold constrained ellipse fitting method for extracting the centroid of laser spot is proposed to monitor the pointing stability of long-period lasers.Based on the above method,the change of laser spot centroid since GF-7 satellite was put into operation is analyzed,and the conclusions obtained have certain reference significance for the quality control of satellite laser altimetry data and the analysis of pointing angle stability.

Application of Three-Dimensional Laser Scanning and Surveying in Geological Investigation of High Rock Slope

The appearance of 3D laser scanning technology is one of the most important technology revolutions in surveying and mapping field. It can be widely used in many interrelated fields, such as engineering constructions and 3D measurements, owing to its prominent characteristics of the high efficiency and high precision. At present its application is still in the initial state, and it is quite rarely used in China, especially in geotechnical engineering and geological engineering fields. Starting with a general introduction of 3D laser scanning technology, this article studies how to apply the technology to high rock slope investigations. By way of a case study, principles and methods of quick slope documentation and occurrence measurement of discontinuities are discussed and analyzed. Analysis results show that the application of 3D laser scanning technology to geotechnical and geological engineering has a great prospect and value.

A new approach to retrieve leaf normal distribution using terrestrial laser scanners

Leaf normal distribution is an important structural characteristic of the forest canopy. Although terrestrial laser scanners（TLS） have potential for estimating canopy structural parameters, distinguishing between leaves and nonphotosynthetic structures to retrieve the leaf normal has been challenging. We used here an approach to accurately retrieve the leaf normals of camphorwood（Cinnamomum camphora） using TLS point cloud data.First, nonphotosynthetic structures were filtered by using the curvature threshold of each point. Then, the point cloud data were segmented by a voxel method and clustered by a Gaussian mixture model in each voxel. Finally, the normal vector of each cluster was computed by principal component analysis to obtain the leaf normal distribution. We collected leaf inclination angles and estimated the distribution, which we compared with the retrieved leaf normal distribution. The correlation coefficient between measurements and obtained results was 0.96, indicating a good coincidence.

Study on the image processing of laser vision seam tracking system

Seam image processing is the basis of the realization of automatic laser vision seam tracking system, and it has become one of the important research directions. Adding windows processing, gray processing, fast median filtering, binary processing and image edge extraction are used to pretreat the seam image. In the post-processing of seam image, the feature points of the target image are succesfully detected by using center line extraction and feature points detection algorithm based on slope analysis. The whole processing time is less than 150 ms, and the real-time processing of seam image can be implemented.

Research on ballistic missile laser SIMU error propagation mechanism

It is necessary that the laser inertial system is used to further improve the fire accuracy and quick reaction capability in the ballistic missile strapdown inertial navigation system. According to the guidance controlling method and the output and error model of ballistic missile laser SIMU, the mathematical model of error propagation mechanism is set up and any transfer environmental function of error coefficient that affects the fire accuracy is deduced. Also, the missile longitudinal/lateral impact point is calculated using MATLAB. These establish the technical foundation for further researching the dispersion characteristics of impact point and reducing the laser guidance error.

基于激光雷达扫描的料仓原料储料量测量方法

为提高仓内原料储料量测量自动化和智能化水平,设计了一种基于二维激光雷达扫描的储料量测量装置与系统。本系统采用RPLIDARS1型二维激光雷达扫描获取不同储料量物料的原始点云数据,通过坐标变换、重叠点提取、滤波、分割等方法对原始点云进行预处理,采用贪婪投影三角化算法将预处理后的点云进行三维重建,获得仓内原料的三维模型,结合物料三维模型和物料的容重获得仓内原料的储料量,从而实现储料量的自动测量。以玉米为试验对象,测量小型储料塔内玉米储料量并对玉米不同储料量进行扫描测量,验证模型的准确性,结果显示:测量结果的平均绝对误差为8.05kg,平均相对误差为1.52%。研究结果表明,基于二维激光雷达扫描的储料量测量方法是可行的,具有较好的稳定性和测量精度,能够满足实际生产需求。

基于多线激光雷达的井下斜坡道无人矿卡定位与建图方法

井下斜坡道的定位与建图是实现井下斜坡道无人驾驶的关键技术之一,矿山井下斜坡道区域为典型非结构化环境特征,且道路具有一定倾斜角度,采用传统SLAM算法无法获得精确里程计信息,导致定位与建图精度难以满足无人矿卡行驶需求。针对上述问题,通过研究激光SLAM(Simultaneous Localization And Mapping)算法LeGO-LOAM,笔者提出一种适用于矿山井下斜坡道环境的定位与建图方法。首先,针对井下斜坡道口两侧均为光滑水泥墙壁,特征点稀少问题,设计了基于人工路标的辅助增强定位方法,有效增加点云特征数量,从而优化位姿估计结果,避免建图漂移现象;然后在特征预处理阶段,提出了一种基于激光点云高度差与坡度信息融合的提取地面点高效算法,通过改善地面地点的选取策略,针对倾斜坑洼路面仍能有效识别地面点,解决了井下斜坡道定位与建图倾斜角度大、误差大等问题;其次,基于CVC(Curved-Voxel Clustering)聚类算法设计了一种斜坡道点云曲率体素聚类算法,采用曲率体素和基于哈希的数据结构对点云进行分割,大幅提高在井下稀疏、噪声环境下点云聚类的鲁棒性;最后,运用Scan-To-Map进行点云匹配,同时兼顾点云配准的性能与速度。在中钢集团山东某井下斜坡道的现场实验证明:与原算法相比精度提升13.15%,Z轴误差降低22.3%,地图质量明显提升,能有效解决井下无人驾驶建图及定位的难题。

Formation energies and electronic structures of native point defects in potassium dihydrogen phosphate

The formation energies and the equilibrium concentration of vacancies, interstitial H, K, P, O and antisite structural defects with P and K in KH2PO4 （KDP） crystals are investigated by ab initio total-energy calculations. The formation energy of interstitial H is calculated to be about 2.06 eV and we suggest that it may be the dominant defect in KDP crystal. The formation energy of an O vacancy （5.25 eV） is much higher than that of interstitial O （0.60 eV）. Optical absorption centres can be induced by defects of O vacancies, interstitial O and interstitial H. We suggest that these defects may be responsible for the lowering of the damage threshold of the KDP. A K vacancy defect may increase the ionic conductivity and therefore the laser-induced damage threshold decreases.

三维重建技术中的高效光条提取方法(特邀)

近年来,三维重建技术在工业检测、医疗成像等领域得到了广泛应用。然而,由于被测物体形状的复杂性以及环境噪声等因素的影响,现有的光条提取算法面临着提取速度慢和重建精度差的挑战。为了解决这些问题,对现有技术进行了深入分析,明确了其在处理复杂形状和噪声干扰时的局限性,提出了一种基于三维重建的高效光条提取(ELE-3D)算法。在ELE-3D算法中,通过Sobel算子精确提取图像边缘,进行二值化处理简化图像复杂性,并利用连通域分析区分噪声与条纹。通过设置面积和长宽比阈值,保留关键特征,来确定感兴趣区域(ROI),精确地识别并提取图像中的特定几何特征区域,同时有效抑制背景噪声,不仅提高了图像的质量,还确保了能够专注于分析图像中最关键的部分。实验结果表明,ELE-3D算法有效地提高了光条提取速度,并有效地抑制了噪声的干扰。在保证重建精度的前提下,测量同一物体相比较于传统的算法Steger和灰度重心法,速度分别提高了89.0%和85.3%。