Automatic Extraction Method of 3D Feature Guidelines for Complex Cultural Relic Surfaces Based on Point Cloud

Cultural relics line graphic serves as a crucial form of traditional artifact information documentation,which is a simple and intuitive product with low cost of displaying compared with 3D models.Dimensionality reduction is undoubtedly necessary for line drawings.However,most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex.Therefore,conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection.Based on the given criteria for assessing surface complexity,this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces.A 2D and 3D combined factor that measured the importance of points on describing surface features,vertex weight,was designed.Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions.The feasibility and stability were verified through experiments conducted on real cultural relic surface data.Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces.The extraction method and the obtained results will be useful for line graphic drawing,displaying and propaganda of cultural relics.

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.

基于PointNet++的邻域特征增强点云语义分割方法

随着智能驾驶、机器人导航等以点云为基础的应用蓬勃发展,点云语义分割逐渐成为研究热点。然而,现有的点云语义分割方法存在局部特征提取不充分、特征融合不完整的缺陷。针对这些不足,提出了对应的解决方案。对于局部特征提取不充分的现象,通过嵌入邻域点的坐标、方向、距离等相关信息去关联邻域点的显式特征。对于特征融合不完整的现象,提出了一种最大池化与自注意力池化相结合的混合池化方法。网络架构基于PointNet++,并结合提出的局部特征提取和融合方法,在S3DIS数据集上的实验结果表明,与基线方法PointNet++相比,各评价指标都有不同程度的提高,证实了新方法的有效性和优越性。

Cloud point extraction coupled with HPLC-UV for the determination of phthalate esters in environmental water samples

A method based on cloud point extraction was developed to determine phthalate esters including di-ethyl-phthalate （DEP）, di- （2-ethylhexyl）-phthalate （DEHP） and di-cyclohexyl-phthalate （DCP） in environmental water samples using high-performance liquid chromatography separation and ultraviolet detection （HPLC-UV）. The non-ionic surfactant Triton X-114 was chosen as extraction solvent. The parameters affecting extraction efficiency, such as concentrations of Triton X-114 and Na2SO4, equilibration temperature, equilibration time and centrifugation time were evaluated and optimized. Under the optimum conditions, the method can achieve preconcentration factors of 35, 88, 111 and detection of limits of 2.0, 3.8, 1.0 ng/ml for DEP, DEHP and DCP in 10-ml water sample, respectively. The proposed method was successfully applied to the determination of trace amount of phathalate esters in effluent water of the wastewater treatment plant and the lixivium of plastic fragments.

Determination of Ultratrace Amounts of Copper(Ⅱ) in Water Samples by Electrothermal Atomic Absorption Spectrometry After Cloud Point Extraction

A novel approach was developed for the determination of ultratrace amounts of copper in water samples by using electrothermal atomic absorption spectrometry （ETAAS） after cloud point extraction （ CPE ）. 1-（ 2-Pyridylazo ） -2- naphthol was used as the chelating reagent and Triton X-114 as the mieellar-forming surfactant. CPE was conducted in a pH 8. 0 medium at 40 ℃ for 10 rain. After the separation of the phases by contrifugafion, the surfactant-rieh phase was diluted with 1 mL of a methanol solution of 0. 1 mol/L HNO3. Then 20μL of the diluted surfactant-rieh phase was injected into the graphite furnace for atomization in the absence of any matrix modifier. Various experimental conditions that affect the extraction and atomization processes were optimized. A detection limit of 5 ng/L was obtained after preconeentration. The linear dynamic range of the copper mass concentration was found to be 0-2.0 ng/mL, and the relative standard deviation was found to be less than 3. 1% for a sample containing 1.0 ng/mL Cu （ Ⅱ ）. This developed method was successfully applied to the determination of uhratraee amounts of Cu in drinking water, tap water, and seawater samples.

Determination of Trace Amounts of Nickel (Ⅱ) by Graphite Furnace Atomic Absorption Spectrometry Coupled with Cloud Point Extraction

A new method based on the cloud point extraction（CPE） for separation and preconcentration of nickel（Ⅱ） and its subsequent determination by graphite furnace atomic absorption spectrometry（GFAAS） was proposed, 8-hydroxyquinoline and Triton X-100 were used as the ligand and surfactant respectively. Nickel（Ⅱ） can form a hy-drophobic complex with 8-hydroxyquinoline, the complex can be extracted into the small volume surfactant rich phase at the cloud point temperature（CPT） for GFAAS determination. The factors affecting the cloud point extraction, such as pH, ligand concentration, surfactant concentration, and the incubation time were optimized. Under the optimal conditions, a detection limit of 12 ng/L and a relative standard deviation（RSD） of 2.9% were obtained for Ni（Ⅱ） determination. The enrichment factor was found to be 25. The proposed method was successfully applied to the determination of nickel（Ⅱ） in certified reference material and different types of water samples and the recovery was in a range of 95%―103%.

Determination of Mecruy at Trace Level in Natural Water Samples by Hydride Generation Atomic Absorption Spectrophotometry after Cloud Point Extraction Preconcentration

A method for the determination of trace mercury in water samples by hydride generation atomic absorption spectrophotometry after cloud point extraction was proposed in the present work. The effects of pH, concentration of surfactant, and equilibration time on cloud point extraction were discussed. The enhancement factor of 20 and the detection limit of 0.039 μg/L were obtained for mercury with relative standard deviation of 4.8% （n = 11）.

Preconcentration of Cadmium in Environmental Samples by Cloud Point Extraction and Determination by FAAS

Cloud point extraction (CPE) has been used for the preconcentration of cadmium, after the formation of a complex with 1, 5-bis(di-2-pyridylmethylene) thiocarbonohydrazide (DPTH), and further determination by flame atomic absorption spectrometry (FAAS) using Triton X-114 as surfactant. The main factors affecting the CPE, such as concentration of Triton X-114 and DPTH, pH, equilibration temperature and incubation time, were optimized for the best extract efficiency. Under the optimum conditions i.e., pH 5.4, [DPTH] = 6x10-3%, [Triton X-114] = 0.25% (v/v), an enhancement factor of 10.5 fold was reached. The lower limit of detection (LOD) obtained under the optimal conditions was 0.95 μg L?1. The precision for 8 replicate deter- minations at 20 and 100 μgL?1 Cd were 2.4 % and 2 % relative standard deviation (R.S.D.). The calibration graph using the preconcentration method was linear with a correlation coefficient of 0,998 at levels close to the detection limit up to at least 200 μgL?1. The method was successfully applied to the determination of cadmium in water, environmental and food samples and in a BCR-176 standard reference material.

Cloud Point Extraction of Polycyclic Aromatic Hydrocarbons in Aqueous Solution with Silicone Surfactants

有二硅酮表面活化剂， Dow Corning DC-190 和 DC-193 的浊点抽取(用户终端设备) 过程，作为 preconcentration 被学习，为水的处理由三踪迹多环芳香烃弄脏(哼) ：蒽，菲和分核。为所有情况，二硅酮表面活化剂获得的充满表面活化剂的阶段的体积是很小的，即在充满表面活化剂的阶段的更低的含水率被获得。例如，不到 3% 起始的答案被获得在一 1%( 由质量) 表面活化剂答案，它是比在一样的表面活化剂集中的 TX-114 的小得多的。并且 TX-114 非在大多数之中作为一个高紧缩的充满表面活化剂的阶段被知道离子型表面活性剂，因此，比较证明优秀丰富被用户终端设备进程与硅酮表面活化剂在分析应用程序保证，并且在充满表面活化剂的阶段获得的更低的含水率在大规模水处理也是重要的。恢复上的添加剂和析相作用方法论的影响哼被讨论。与 DC-193 作比较。DC-190 有一个下浊点和所有的更高的恢复(近的 100%) 三在一样的表面活化剂集中哼，它在 HPLC 以前作为 preconcentration 进程为申请被要求系统。然而， DC-190 答案是难的是而 DC-193 有一个相对更高的阶段由加热，而是一个高浊点分开速度，仅仅由加热分开的阶段(在 360K 附近) 限制它的申请。由于由加热的析相作用是对大规模水处理合适的用户终端设备的唯一的方法，二个硅酮表面活化剂答案的混合物在这研究被调查。包含 1% 混合 DC-190 和 DC-193 的一个答案(在 90:10 的比率) 有分开的一个相对低浊点和快阶段的 100% 附近的移开的蒽，菲和分核加速。

A New Thioamide Derivative for Separation and Preconcentration of Multi Elements in Aquatic Environment by Cloud Point Extraction

2-(pyridine-2-yl)-N-p-chlorohydrazinecarbothioamide (HCPTS) was synthesized, characterized and successfully applied for the preconcentration of Cu(II), Ni(II), Zn(II), Cd(II), Co(II), Pb(II), Fe(II), and Hg(II) in water, blood, and urine samples prior to graphite furnace atomic absorption determination (GFAAS);Hg was determined by cold vapor technique. Under the optimum experimental conditions (i.e. pH = 8, 10–4 M of HCPTS, 0.05% w/v of Triton X-114), calibration graphs were linear in the range of 0.02 to 200 ng?mL–1 for Co(II), Cd(II), Pb(II) and Ni(II);0.03 to 200 ng?mL–1 for Cu(II);0.07 to 200 ng?mL–1 for Fe(II) and Zn(II) and 0.02 to 150 ng?mL–1 for Hg(II). The enrichment factors were 43, 51, 41, 46, 54, 40, 45 and 52 for Cu(II), Ni(II),Zn (II), Cd(II), Co(II), Pb(II), Fe(II), and Hg(II), respectively. The limit of detection were found to be 0.019, 0.094, 0.0514, 0.052, 0.0165, 0.047, 0.068 and 0.041 ng?mL–1 for Cu(II), Ni(II), Zn(II), Cd(II), Co(II), Pb(II), Fe(II), and Hg(II), respectively. The developed method was applied to the determination of these metal ions in water, blood and urine samples with satisfactory results.

Cloud-point extraction and preconcentration of bisphenol A from water samples

A novel cloud-point extraction (CPE) was successfully used in preconcentration of biphenol A (BPA) from aqueous solutions. Majority of BPA is extracted into the surfactant-rich phase. The parameters affecting the CPE such as concentration of surfactant and electrolyte, equilibration temperature and time and pH of sample solution were investigated. The samples were analyzed by high-performance liquid chromatography with ultraviolet detection. Under the optimized conditions, preconcentration of 10 mL sample gives a preconcentration factor of 11. The limit of detection (LOD) and limit of quantification (LOQ) are 0.1 μg/L and 0.33 μg/L, respectively. The linear range of the proposed method is 0.2-20 μg/L with correlation coefficients greater than 0.998 7 and the spiking recoveries are 97.96%-100.42%. The interference factor was tested and the extraction mechanism was also investigated. Thus, the developed CPE has proven to be an efficient, green, rapid and inexpensive approach for extraction and preconcentration of BPA from water samples.

Extraction of Sodium Copper Chlorophyll in Food Samples Based on Cloud Point Extraction with a Nonionic Surfactant

A new method was developed for the determination of sodium copper chlorophyll(SCC) by cloud point extraction preconcentration and spectrophotometry, for which Triton X-114 was selected as a nonionic surfactant. Several factors affecting the extraction efficiency of SCC and its subsequent determination, including the p H of the sample solution, salt and surfactant concentrations, and equilibration temperature and time, were studied and optimized. The extraction efficiency approached 99.4%.The calibration graph under the optimum conditions was linear in the concentration range of 3–220 mg/L with correlation coefficients> 0.9997(n = 8). The limit of detection for the analytes was 0.6 mg/L(S/N = 3). The proposed method is inexpensive, simple, and accurate for the extraction and determination of SCC in food samples.

Recovery of polyphenols from camu-camu(Myrciaria dubia H.B.K.McVaugh)depulping residue by cloud point extraction

In this study the potential of cloud point extraction formed by a non-ionic surfactant was used in order to separate polyphenols from industrial residues of camu-camu. The effects of operational conditions of the cloud point extraction(CPE) on the polyphenol recovery and volumetric ratio were investigated. The results showed a maximum recovery of 95.71% that was obtained using 7.0 wt% Triton X-114, native pH(3.25), and 80 wt%polyphenol extract at 30 °C. The use of cloud point extraction was successful to recover the polyphenols from agroindustrial residue since it is a simple as well as of low-cost technique.

Determination of Lisinopril in Bulk and Pharmaceutical Formulations by Cloud Point Extraction—A Green Method

A sensitive and eco-friendly method was developed for the spectrophotometric determination of Lisinopril (LSP) in bulk and pharmaceutical formulations by cloud point extraction technique. The method was based on the formation of a blue-colored coordination complex between Lisinopril (LSP) and Cobalt Thiocyanate (CTC) at a suitable pH. The Complex in aqueous medium was extracted into surfactant layer by cloud point extraction using a non-ionic surfactant Triton X-114 and then the surfactant layer was dissolved in a suitable volume of ethanol and the amount of Lisinopril was determined spectrophotometrically at a wavelength of 625 nm. The conditions like concentration of the drug, concentration of CTC and of Triton X-114, PH, etc. were optimized by OFAT (One Factor At a Time) method. The linear range of calibration curve was 1 - 6 μg/ml and the linear regression equation with a correlation coefficient of 0.99996 was y = 0.0021 + 0.084x. Preconcentration and enrichment factors were found to be 100 and 3.12 respectively, achieving the detection limit of 0.0588 μg/ml. The proposed method was successfully applied for the determination of LSP in the drug formulations. The obtained values were in agreement with the values as quoted by the manufacturers.

Determination of Selenium in Water by Vortex-Assisted Cloud-Point Extraction Combination with Fluorescence Detection

A simple vortex-assisted cloud-point extraction(VA-CPE)method combined with the fluorescence(FL)strategy was developed to extract and determine inorganic Se(IV)in environmental water.Toluene was used as an extraction reagent,and Se(VI)was reduced to Se(IV)by subjecting its solution in 4 mol/L HCl to microwave heating for generating a yellow piazselenol complex using 3,3'-diaminobenzidine(DAB)and Se(IV).The concentration of the complex exhibited an excellent linear relation with the FL at 560 nm with an excitation wavelength of 420 nm.In addition,the effects of the toluene volume,pH,and VA-CPE parameters were investigated and the interference from coexisting ions was also studied.This method was successfully applied to determine the concentration selenium in environmental water samples with a detection limit of 0.05μg/L in the line range from 0.50μg/L to 50.00μg/L.

A Novel Airborne 3D Laser Point Cloud Hole Repair Algorithm Considering Topographic Features

Hole repair processing is an important part of point cloud data processing in airborne 3-dimensional(3D)laser scanning technology.Due to the fragmentation and irregularity of the surface morphology,when applying the 3D laser scanning technology to mountain mapping,the conventional mathematical cloud-based point cloud hole repair method is not ideal in practical applications.In order to solve this problem,we propose to repair the valley and ridge line first,and then repair the point cloud hole.The main technical steps of the method include the following points:First,the valley and ridge feature lines are extracted by the GIS slope analysis method;Then,the valley and ridge line missing from the hole are repaired by the mathematical interpolation method,and the repaired results are edited and inserted to the original point cloud;Finally,the traditional repair method is used to repair the point cloud hole whose valley line and ridge line have been repaired.Three experiments were designed and implemented in the east bank of the Xiaobaini River to test the performance of the proposed method.The results showed that compared with the direct point cloud hole repair method in Geomagic Studio software,the average repair accuracy of the proposed method,in the 16 m buffer zone of valley line and ridge line,is increased from 56.31 cm to 31.49 cm.The repair performance is significantly improved.

WADE-Net: Weighted Aggregation with Density Estimation for Point Cloud Place Recognition

Point cloud based place recognition plays an important role in mobile robotics. In this paper, we propose a weighted aggregation method from structure information adaptively for point cloud place recognition. Firstly, to preserve the prior distributions and local geometric structures, we fuse learned hidden features with handcrafted features in the beginning. Secondly, we further extract and aggregate adaptively weighted features concerning density and relative spatial information from these fused features, named Weighted Aggregation with Density Estimation (WADE) module. Then, we conduct the WADE block iteratively to group the latent manifold structures. Finally, comparison results on two public datasets Oxford Robotcar and KITTI show that the proposed approach exceeds the comparison approaches on recall rate averagely 7% - 8%.

基于PointCNN的车载行道树点云分割方法

利用点云卷积网络(PointCNN)为语义分割算法基础处理无序点云来提取行道树点云,经过模型建立、样本训练、点云分割等步骤从地物点云中精确分割出行道树点云,并对三个数据集的应用结果作精度评定,其最终结果的误差在有效范围内,并对PointCNN中的参数进行分析,完善算法的应用以适应于道路环境下行道树点云的提取。本次研究中考虑到训练各类型行道树类型,且受非行道树点云目标干扰小,在复杂道路环境下的数据分割工作有很好的效果。

基于RS-Conv的多尺度神经网络LiDAR点云断裂带提取方法

断裂带与地震、滑坡等自然灾害的发生有着密切关系,精准提取断裂带不仅可为地震断层的定量化研究提供指导,还可为地震灾害风险评估及防震减灾决策的制定提供科学依据。针对现有方法中LiDAR点云断裂带提取不完整、连续性差及错误率高等问题,文中提出了一种基于RS-Conv的多尺度神经网络LiDAR点云断裂带提取方法,以便更好地解决复杂地形区域的断裂带自动提取问题。该方法首先构建不同空间尺度的邻域点集,从而更全面地考察点云的局部几何结构特征。考虑到RS-Conv算子能够很好地表征中心点与邻域点的空间关系,文中以RS-Conv算子作为卷积模块构建了多尺度神经网络模型,以提取出LiDAR点云不同尺度的深层次特征,对其进行堆叠并输入到全连接层,以完成对断裂带点的提取。最后,在ISPRS点云数据集、川滇点云数据集和鲜水河数据集上对文中所述方法与张量分解方法和Deep Neural Networks(DNN)方法进行了对比实验,结果表明,文中方法的分类精度最高,分类总误差最低仅为0.3%,较其他方法降低了0.91%~2.79%,证实了该方法在点云断裂带提取方面的优越性。