3D cavity detection technique and its application based on cavity auto scanning laser system

Ground constructions and mines are severely threatened by ones. Safe and precise cavity detection is vital for reasonable cavity underground cavities especially those unsafe or inaccessible evaluation and disposal. The conventional cavity detection methods and their limitation were analyzed. Those methods cannot form 3D model of underground cavity which is used for instructing the cavity disposal; and their precisions in detection are always greatly affected by the geological circumstance. The importance of 3D cavity detection in metal mine for safe exploitation was pointed out; and the 3D cavity laser detection method and its principle were introduced. A cavity auto scanning laser system was recommended to actualize the cavity 3D detection after comparing with the other laser detection systems. Four boreholes were chosen to verify the validity of the cavity auto scanning laser system. The results show that the cavity auto scanning laser system is very suitable for underground 3D cavity detection, especially for those inaccessible ones.

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.

An improved bicubic imaging fitting algorithm for 3D radar detection target

3D ground-penetrating radar has been widely used in urban road underground disease detection due to its nondestructive,efficient,and intuitive results.However,the 3D imaging of the underground target body presents the edge plate phenomenon due to the space between the 3D radar array antennas.Consequently,direct 3D imaging using detection results cannot reflect underground spatial distribution characteristics.Due to the wide-beam polarization of the ground-penetrating radar antenna,the emission of electromagnetic waves with a specific width decreases the strong middle energy on both sides gradually.Therefore,a bicubic high-precision 3D target body slice-imaging fitting algorithm with changing trend characteristics is constructed by combining the subsurface target characteristics with the changing spatial morphology trends.Using the wide-angle polarization antenna’s characteristics in the algorithm to build the trend factor between the measurement lines,the target body change trend and the edge detail portrayal achieve a 3D ground-penetrating radar-detection target high-precision fitting.Compared with other traditional fitting techniques,the fitting error is small.This paper conducts experiments and analyses on GpaMax 3D forward modeling and 3D ground-penetrating measured radar data.The experiments show that the improved bicubic fitting algorithm can eff ectively improve the accuracy of underground target slice imaging and the 3D ground-penetrating radar’s anomaly interpretation.

3D Depth Measurement for Holoscopic 3D Imaging System

Holoscopic 3D imaging is a true 3D imaging system mimics fly’s eye technique to acquire a true 3D optical model of a real scene. To reconstruct the 3D image computationally, an efficient implementation of an Auto-Feature-Edge (AFE) descriptor algorithm is required that provides an individual feature detector for integration of 3D information to locate objects in the scene. The AFE descriptor plays a key role in simplifying the detection of both edge-based and region-based objects. The detector is based on a Multi-Quantize Adaptive Local Histogram Analysis (MQALHA) algorithm. This is distinctive for each Feature-Edge (FE) block i.e. the large contrast changes (gradients) in FE are easier to localise. The novelty of this work lies in generating a free-noise 3D-Map (3DM) according to a correlation analysis of region contours. This automatically combines the exploitation of the available depth estimation technique with edge-based feature shape recognition technique. The application area consists of two varied domains, which prove the efficiency and robustness of the approach: a) extracting a set of setting feature-edges, for both tracking and mapping process for 3D depthmap estimation, and b) separation and recognition of focus objects in the scene. Experimental results show that the proposed 3DM technique is performed efficiently compared to the state-of-the-art algorithms.

Monitoring slope deformation using a 3-D laser image scanning system: a case study

An ILRIS-36D 3-D laser image scanning system was used to monitor the Anjialing strip mine slope on Pingshuo in Shanxi province. The basic working principles, performance indexes, features and data collection and processing methods are illus-trated. The point cloud results are analyzed in detail. The rescale range analysis method was used to analyze the deformation char-acteristics of the slope. The results show that the trend of slope displacement is stable and that the degree of landslide danger is low. This work indicates that 3-D laser image scanning can supply multi-parameter, high precision real time data over long distances. These data can be used to study the distortion of the slope quickly and accurately.

3D FEM simulation of responses of LWD multi-mode resistivity imaging sonde

A new multi-mode resistivity imaging sonde, with toroidal coils as source, can conduct three resistivity measurements: azimuthal resistivity, lateral resistivity, and bit resistivity measurements. Thus, the logging time and cost are greatly saved. The toroidal coils are simplified as an extended voltage dipole and the response equations are derived for a homogenous formation. Based on 3D FEM, the depth of investigation(DOI), vertical resolution, circumferential azimuthal capacity, borehole diameter, mud resistivity, thickness of target formation, and the resistivity of the surrounding formation and mud invasion are simulated. The results suggest that the three measurement modes of the new sonde are different in vertical resolutions and DOIs. The circumferential detection ability of the azimuth button depends on the contrast between the anomaly and formation resistivity and the open angle of the anomaly. Whether the borehole is truncated at the bit or not has a great influence on the simulation results. The borehole and mud invasion affect the apparent resistivity in all modes, but the effects of resistivity of surrounding formation and thickness of the target formation are only corrected for lateral resistivity measurement.

3D particle tracking velocimetry for the determination of temporally resolved particle trajectories within laser powder bed fusion of metals

Within this work,we present a system for the measurement of the three-dimensional(3D)trajectories of spatters and entrained particles during laser powder bed fusion(L-PBF)of metals.It is comprised of two ultrahigh-speed cameras and a reconstruction task specific processing reconstruction algorithm.The system enables an automated determination of 3D measures from the trajectories of a large number of tracked particles.Ambiguity evolving from an underdetermined geometrical situation induced by a two-camera setup is resolved within the tracking using a priori knowledge of L-PBF of metals.All processing steps were optimized to run on a graphics processing unit to allow the processing of large amounts of data within an appropriate time frame.The overall approach was validated by a comparison of the measurement results to synthetic images with a known 3D ground truth.

32×32 Si盖革模式激光焦平面探测器

为了满足350 nm~1100 nm波长范围内远距离及微弱激光3维成像探测的需求,提出了一种规模为32×32的盖革模式硅激光焦平面阵列探测器,它主要由硅雪崩光电二极管阵列、读出电路芯片、微透镜阵列、半导体制冷器、引脚网格阵列壳体等元件组成。硅雪崩光电二极管焦平面阵列采用拉通型N^(+)-Π_(1)-P^(-)-Π_(2)-P^(+)结构,工作在盖革模式下,通过Si片背面抛磨减薄及盲孔刻蚀技术,实现了纤薄光敏区的加工;读出电路采用主动模式淬灭设计,使电路单元的死时间控制在50 ns以内,并利用一种带相移技术的时间数字转换电路优化方案,在满足时间分辨率不大于2 ns的同时,降低了读出电路芯片的功耗。结果表明,在反向过偏电压14 V、工作温度-40℃的条件下,该探测器在850 nm的目标波长可实现20.7%的平均光子探测效率与0.59 kHz的平均暗计数率,时间分辨率为1 ns,有效像元率优于97%。该研究为纤薄型背进光Si基激光焦平面探测器的研制提供了参考。

机载激光3D探测成像系统的发展现状

机载激光3D探测成像是通过激光主动成像产生目标的角-角-距、角-角-速度3D图像的一种新的探测成像技术。本文重点阐述了机载激光3D探测成像系统的原理、功能和系统的组成。介绍了该系统在军事和民用两大领域的应用,详细地讨论了近几年机载激光3D探测成像技术的国内外发展现状及动态,总结了该项技术的发展方向。认为国外的机载激光3D探测系统正向远距离、高分辨率、轻量化、低功耗、高实时性和人眼安全方向发展,而目前国内的相关研究仍处于实验室阶段,与国外相比还存在一定差距。文章最后以用户需求为例,从设计的角度对机载激光3D探测成像系统进行了分析,讨论了该系统在测距机制、扫描机构、探测器、数据处理和显示等方面的处理。

机载激光3D探测成像系统的关键技术

介绍了机载激光3D探测成像系统的应用领域和国内外发展现状,概括了小型无人机载激光3D成像检测系统(JIGSAW)、机载激光测深系统(LADS)、直升机3D-LZ Imaging LADAR及机载对地高分辨详查系统的基本组成、技术指标以及各自的特点。阐述了激光3D成像系统的工作原理与扫描方式的分类,并重点对其单元核心技术即激光测距系统、激光光轴控制与指向测量系统、数据图像处理技术与显示系统进行了研究。最后,简单综述了机载激光3D探测成像系统的发展前景。

Laser Scanning的基本原理及其应用前景

首先介绍了激光测距仪的发展历程,针对应用领域的不同,分别对3维激光成像仪和机载/星载激光测高仪的测量原理进行了阐述,并分别介绍了两种激光测距仪的工作流程以及数据处理流程,最后对两种激光测距仪的应用范围进行了阐述,并把两种激光测距技术和普通摄影测量进行了比较,指出了激光测距技术相对于普通摄影测量的优点,即高精度性、穿透性、实时性。

三维激光3D打印技术在数字化重现中的应用

为了提高3D模型多媒体数字化重现的逼真性以及多媒体数字信息的三维表达能力,提出一种基于三维激光3D打印的多媒体数字化重现技术。首先采用三维激光3D打印技术进行多媒体数字信息的图像采样,进行多媒体数字模型的三维激光成像的边缘轮廓特征提取,利用激光3D打印的三维离散点数据重构出多媒体图像的视觉模型。然后采用Taubin平滑算子进行三维激光3D图像的平滑处理,在三维非线性空间中修正数字化3D激光打印图像的局部细节,使得输出的数字化三维激光图像更好地贴合真实的3D模型。最后进行实际3D数字化重现的仿真实验,结果表明,采用该方法进行3D打印数字化重现,输出三维激光图像的信噪比较高,归一化误差较低,数字化重现的视觉效果较好。

Laser speckle contrast imaging based on uniting spatiotemporal Fourier transform

We propose a laser speckle contrast imaging method based on uniting spatiotemporal Fourier transform.First,the raw speckle images are entirely transformed to the spatiotemporal frequency domain with a three-dimensional(3D)fast Fourier transform.Second,the dynamic and static speckle components are extracted by applying 3D low-pass and high-pass filtering in the spatiotemporal frequency domain and inverse 3D Fourier transform.Third,we calculate the time-averaged modulation depth with the average of both components to map the two-dimensional blood flow distribution.The experiments demonstrate that the proposed method could effectively improve computational efficiency and imaging quality.

3D Bounding Box Proposal for on-Street Parking Space Status Sensing in Real World Conditions

Vision-based technologies have been extensively applied for on-street parking space sensing,aiming at providing timely and accurate information for drivers and improving daily travel convenience.However,it faces great challenges as a partial visualization regularly occurs owing to occlusion from static or dynamic objects or a limited perspective of camera.This paper presents an imagery-based framework to infer parking space status by generating 3D bounding box of the vehicle.A specially designed convolutional neural network based on ResNet and feature pyramid network is proposed to overcome challenges from partial visualization and occlusion.It predicts 3D box candidates on multi-scale feature maps with five different 3D anchors,which generated by clustering diverse scales of ground truth box according to different vehicle templates in the source data set.Subsequently,vehicle distribution map is constructed jointly from the coordinates of vehicle box and artificially segmented parking spaces,where the normative degree of parked vehicle is calculated by computing the intersection over union between vehicle’s box and parking space edge.In space status inference,to further eliminate mutual vehicle interference,three adjacent spaces are combined into one unit and then a multinomial logistic regression model is trained to refine the status of the unit.Experiments on KITTI benchmark and Shanghai road show that the proposed method outperforms most monocular approaches in 3D box regression and achieves satisfactory accuracy in space status inference.

Ultrasonic signal detection based on Fabry–Perot cavity sensor

Acoustic/ultrasonic sensors are devices that can convert mechanical energy into electrical signals.The Fabry–Perot cavity is processed on the end face of the double-clad fiber by a two-photon three-dimensional lithography machine.In this study,the outer diameter of the core cladding was 250μm,the diameter of the core was 9μm,and the microcavity sensing unit was only 30μm.It could measure ultrasonic signals with high precision.The characteristics of the proposed ultrasonic sensor were investigated,and its feasibility was proven through experiments.Its design has a small size and can replace a larger ultrasonic detector device for photoacoustic signal detection.The sensor is applicable to the field of biomedical information technology,including medical diagnosis,photoacoustic endoscopy,and photoacoustic imaging.

密文域下3D激光雷达图像认证方法研究

加密认证3D激光雷达图像,可提高图像传输中的安全性能。针对传统的加密认证算法密钥空间较小,安全性不高的问题,提出一种基于分段线性混沌映射的密文域下3D激光雷达图像认证方法。在混沌系统中构建3D激光雷达图像的密文域并进行Hash计算,对加密图像RGB分解后得到三个灰度图像,对三个图像分别使用不同的高维混沌序列进行分段线性特征映射,产生加密序列,把加密后的图像进行像素位置置乱后重组其特征,在密文域下生成认证密钥,实现3D激光雷达图像认证。仿真结果表明,采用该方法进行3D激光雷达图像加密认证,具有很强的像素去相关性,密钥空间大,密钥的敏感性提高,加密认证性能好。

Contour Detection-Based Realistic Finite-Difference-Time-Domain Models for Microwave Breast Cancer Detection

In this paper, a collection of three-dimensional(3D)numerical breast models are developed based on clinical magnetic resonance images(MRIs). A hybrid contour detection method is used to create the contour, and the internal space is filled with different breast tissues, with each corresponding to a specified interval of MRI pixel intensity. The developed models anatomically describe the complex tissue structure and dielectric properties in breasts. Besides, they are compatible with finite-difference-time-domain(FDTD)grid cells. Convolutional perfect matched layer(CPML)is applied in conjunction with FDTD to simulate the open boundary outside the model. In the test phase, microwave breast cancer detection simulations are performed in four models with varying radiographic densities. Then, confocal algorithm is utilized to reconstruct the tumor images. Imaging results show that the tumor voxels can be recognized in every case, with 2 mm location error in two low density cases and 7 mm─8 mm location errors in two high density cases, demonstrating that the MRI-derived models can characterize the individual difference between patients' breasts.

Segmenting Salient Objects in 3D Point Clouds of Indoor Scenes Using Geodesic Distances

Visual attention mechanisms allow humans to extract relevant and important information from raw input percepts. Many applications in robotics and computer vision have modeled human visual attention mechanisms using a bottom-up data centric approach. In contrast, recent studies in cognitive science highlight advantages of a top-down approach to the attention mechanisms, especially in applications involving goal-directed search. In this paper, we propose a top-down approach for extracting salient objects/regions of space. The top-down methodology first isolates different objects in an unorganized point cloud, and compares each object for uniqueness. A measure of saliency using the properties of geodesic distance on the object’s surface is defined. Our method works on 3D point cloud data, and identifies salient objects of high curvature and unique silhouette. These being the most unique features of a scene, are robust to clutter, occlusions and view point changes. We provide the details of the proposed method and initial experimental results.

Wavelength-dependent three-dimensional single-molecule superlocalization imaging for yoctomole detection of thyroid-stimulating hormone on a quantum dot nanobiosensor

A wavelength-dependent three-dimensional(3D)superlocalization imaging method on gold nanoislands(GNIs)chip was developed as a supersensitive single-molecule thyroid-stimulating hormone(TSH)nanobiosensor.Scattered and fluorescent signals from gold nanoislands on the substrate and quantum dots(QDs)nanoprobes were simultaneously isolated and acquired within an evanescent field layer generated by total internal reflection(TIR)of incident light using a dual-view device.The 3D TIR fluorescence images of TSH-bound QDs on the GNIs were obtained using z-axis optical sectioning at 10nm intervals before/after immunoreaction to identify the optimal conditions for detection.The localized centroid position of QD nanoprobes and GNI were distinguished at a subdiffraction limit resolution using 3D Gaussian fitting to the point spread function.The QD TSH nanobiosensor using wavelength-dependent 3D TIR fluorescence-based single-molecule localization microscopy(3D TIRF-SLM)imaging technique showed an excellent detection limit of 90 yoctomoles(~54 molecules)and a wide linear dynamic range of 1.14 zmol/L-100 pmol/L for TSH.The detection sensitivity was about 4.4×10^(9)times higher than conventional enzyme-linked immunosorbent assay and could successfully quantify TSH in human serum.The wavelength-dependent 3D TIRF-SLM technique may emerge as a reliable platform for ultrahigh-sensitive nanobiosensors at the single-molecule level and early diagnosis with quantification of disease-related ultra-tracebiomolecules.

FORSAT:a 3D forest monitoring system for cover mapping and volumetric 3D change detection

A 3D forest monitoring system,called FORSAT(a satellite very high resolution image processing platform for forest assessment),was developed for the extraction of 3D geometric forest information from very high resolution(VHR)satellite imagery and the automatic 3D change detection.FORSAT is composed of two complementary tasks:(1)the geometric and radiometric processing of satellite optical imagery and digital surface model(DSM)reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery,(2)3D surface comparison for change detection.It allows the users to import DSMs,align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes(together with precision values)between epochs.FORSAT is a single source and flexible forest information solution,allowing expert and non-expert remote sensing users to monitor forests in three and four(time)dimensions.The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation,clear-cut and fire severity mapping.The capacity and benefits of FORSAT,as a forest information system contributing to the sustainable forest management,have been tested and validated in case studies located in Austria,Switzerland and Spain.