三维激光彩色扫描仪中展开图的获取及拼接方法研究

根据三维激光彩色扫描仪的特点,提出了一种从彩色图像序列中获取物体表面颜色展开图的算法,并在此基础上实现了一种对多次扫描获取的展开图进行拼接的方法。实验的结果令人满意。     

激光三维扫描仪的硬件设计与实现

非接触三维测量技术是研究物体形态，特别是研究软组织物体表面形态的基础，如何在非接触条件下精确地采集三维数据，这一直是人们所期待要解决的问题，激光三维扫描仪较好地解决了这一问题，可方便、快速、精确地采集各类物体表面的三维数据。利用这组三维数据，计算机可再现出物体任一角度的三维图像，从而为研究物体表面形态打下良好的基础。     

基于三维激光扫描仪的排土场快速建模

排土场一旦发生事故,不仅影响到矿山的正常生产,也将使矿山蒙受巨大的经济损失,因此,定期对排土场进行容积测算、应力分析显得尤为重要。利用三维激光扫描仪,可以快速获取排土场的三维点云数据,进而利用快速自动配准算法,建立排土场的完整点云模型。利用该数据,可以方便的计算排土场容积,并针对性的进行应力分析,预测排土场的形变趋势,及时预防,矿山的安全生产。     

三维激光扫描仪分辨率的测试方法

为获取便携式三维激光扫描仪分辨率与扫描范围间的量化关系,以Creaform公司的Handyscan EXAscan扫描仪获取标准块在不同分辨率等级下的点云数据,应用逆向校核软件Geomagic Qualify测试试验数据样本,并采用方差分析和加权平均的统计方法分析样本数据。试验结果显示,EXAscan扫描仪的四级分辨率与扫描范围间均呈线性关系,且拟合度均超过0.979,该测试方法可快速有效地判别三维激光扫描仪的分辨率水平。     

Z Corp推出两款突破性三维扫描仪

2009年2月9日,本刊讯,Z Corporation公司发布了两部手持型激光扫描仪产品——ZScanner 700 PX和ZScanner 700CX,它们可以帮助用户更快更容易地捕捉大量的三维图像数据,主要可用于逆向工程、检测、产品设计等领域.     

三维激光彩色扫描系统的研究

本文介绍了三维重建的主要方法,在此基础之上详细之上详细介绍了我们研制的三维激光彩色扫描系统的基本原理,在硬件及其控制部分和软件处理部分中分别介绍了这两部分的原理及实现方法,最后给出了实验结果。     

三维扫描仪在仿真饰品镍释放量检测中的应用

在仿真饰品的镍释放量的检测中,样品表面积的测量一直是其难点。自仿真饰品2011年纳入法定检验目录后,就更加迫切地需要解决此问题。将三维扫描仪应用于仿真饰品镍释放量的检测,通过对样品的三维再构,借助计算机快速准确地测量样品的表面积,为此问题的解决提出了圆满的方案。     

三维全身扫描仪的建模仿真

随着计算机全面进入3D时代,三维全身扫描系统对社会的价值越来越显著,获取人体表面的三维几何信息,是建立3D人体模型的先决条件。该文提出了一种基于结构光方法的三维全身扫描仪的系统仿真方案,使用3D Studio MAX软件仿真得到虚拟扫描头运动形成的带激光条纹的图像序列,最后用仿真数据进行三维重建。关键步骤包括用自适应阈值法提取激光带中心,深度图像的获取,以及多扫描头数据的融合等。实验取得了满意的效果,获得了人体的完整轮廓线,验证了系统仿真方案的合理性与高效性。     

基于激光扫描仪的树干三维重建方法研究

本文介绍了一种利用三维激光扫描仪,对树木枝干进行三维重建的方法.首先利用激光扫描仪获取一系列树木枝干的坐标数据,继而通过筛选这些数据来重建一系列树木枝干的片断模型,最后利用所得到的这些片断模型进行拼合,从而得到完整枝干的三维模型.利用这种方法重建出来的枝干模型是一系列圆柱体经过空间的叠加而构成的.这种三维重建方法所得到的模型可用于树胸高度的测量以及树干锥度和倾斜度的估算等领域,在实际应用中取得了良好的效果.     

接触式多关节三维扫描仪研究

论述了拥有自主知识产权的接触式多关节三维扫描仪3DLCS-400的硬件系统和软件系统的基本构成、主要特点和实现方法。在此基础上,研究了接触式三维信息获取中的一些关键技术———数据采集与三维显示的同步、坐标计算和误差校正、三维构型重建。采用基于API函数的异步多线程串行通信和OpenGL三维显示技术,提出了一种修正最小二乘法和基因可变限改进遗传算法相结合的参数标定方法和运用轮廓线的三维散乱数据构型方法。该产品的研制成功填补了国产三维信息获取系统的一个空白。     

三度等效推理

本文重点讨论三度等效推理技术,三度等效推理通过时间强度系数,空间偏移系数和概念转换系数较为全面准确地刻划了天气系统在时间、空间和性态方面的发展演变过程,它在一定程度上,克服了以往专家系统的性能脆弱性,提高了专家系统对初始证据和中间假设的适应力。     

均值聚类在三维重构图像预处理中的应用

本文详细叙述了基于均值聚类算法的图像分割技术,并将该分割结果应用于三维医学器官重构并比较其重构效果,实验结果证明,通过应用该算法的三维医学图像重构,人体各个组织器官能够更加清晰地被分割出来,从而极大限度地提高了器官组织重构的正确性,为拟定最佳手术方案提供可靠依据。     

3Dsurs中激光扫描仪工作平台的姿态纠正

实现三维空间数据的动态、快速、准确和批量的获取,一个重要的问题在于动态测量过程中传感器工作平台的姿态纠正。该研究利用差分全球卫星定位系统进行姿态测量和动态定位,然后对激光扫描仪数据进行姿态纠正和空间整合,以获取扫描目标的三维空间信息,并自主研发了相应的数据处理系统。经过实验验证,能够满足实际应用的需要。     

三维螺纹造型的一种计算机建模方法

三维形体的计算机造型是计算机图形学的一个重要研究领域。三维螺纹是在科学技术和工程领域应用很广泛的一种较为复杂的形体。正因为其复杂,所以它在计算机上建模比较困难。本文具体地分析了螺旋线的形成过程、原理和螺旋线的数学模型以及螺纹车削成形的整个过程,在此基础上,建立了三维螺纹的一种计算机建模方法。从该方法的应用实践来看,本文提出的方法是成功的,效率也很高,具有较强的实用价值和良好的推广应用前景。     

移动机器人导航中激光雷达测距性能研究

距离检测是移动机器人导航的一个关键问题.文章介绍了基于飞行时间法测距的二维激光雷达LMS291的工作原理,分析了影响LMS291测距性能的误差因素,通过统计分析对测距数据进行标定,研究了不同物体表面属性对测距精度的影响;通过混合像素测定方法确定LMS291的角度分辨率;通过对激光雷达测距性能的试验,建立测距误差模型.所得结论可以为复杂非结构化环境下移动机器人导航中障碍检测、环境建模及自定位提供支持.     

激光显示中颜色系统的校正

激光显示作为一种新的显示技术它日益受到人们的关注。但是现有的显示制式只支持现有的显示系统当中的颜色转换,不支持激光显示的颜色转化,为了发挥激光显示色纯度高、色饱和度好、亮度高等优点,需要重新建立了一套适合激光显示的颜色转换系统。本文采用多元回归法来实现从CRT显示器到激光显示色域的转变,主要研究了实验样本数目、检验样本数目对结果的影响,采用了DPS数学软件系统对实验数据进行分析处理,建立了二阶多元回归的数学模型,并分析了模型的误差。选用二阶多元回归来预测和校正激光显示的显示效果,预测效果良好,误差较小。     

Color Distribution - A New Approach to Texture Compression

Texture compression is recently one of the most important topics of 3D scene rendering techniques, because it allows rendering more complicated high-resolution scenes. However, because of some special requirements for these type of techniques, the commonly used block decomposition approach may introduce visual degradation of image details due to lack of colors. We present here a new approach to texture compression, which allows sharing of one color by several blocks providing a larger number of unique colors in each particular block and the best compression ratio. We also present an iterative algorithm for obtaining distributed colors on a texture, and discuss some advantages of our approach. The paper concludes with comparison of our technique with S3TC and other block decomposition methods.     

Cooperative Fusion for Multi-Obstacles Detection With Use of Stereovision and Laser Scanner

We propose a new cooperative fusion approach between stereovision and laser scanner in order to take advantage of the best features and cope with the drawbacks of these two sensors to perform robust, accurate and real time-detection of multi-obstacles in the automotive context. The proposed system is able to estimate the position and the height, width and depth of generic obstacles at video frame rate (25 frames per second). The vehicle pitch, estimated by stereovision, is used to filter laser scanner raw data. Objects out of the road are removed using road lane information computed by stereovision. Various fusion schemes are proposed and one is experimented. Results of experiments in real driving situations (multi-pedestrians and multi-vehicles detection) are presented and stress the benefits of our approach.Raphaël Labayrade was born in France, in 1976. He received the M.S. degree in 2000 from the university of Saint Etienne, and he was also graduate from the ENTPE engineer school in 2000. In 2004 he received the Ph.D. degree from the university Pierre et Marie Curie Paris VI. In his thesis he proposed a new approach for detecting road obstacles using stereovision in a generic, fast and robust manner.He is currently a researcher at INRETS since 2004 in the perception team of the LIVIC department and works on automated highway and on on-board driving assistance systems. His main work deals with obstacles detection using data fusion but he is also interested in road lane recognition. He is involved for vision tasks in various european and french projects dealing with intelligent vehicles (Carsense, Micado, Arcos). He teaches at Jussieu (Paris VI), Ecole Nationale des Ponts et Chaussées, University of Versailles.He is the author and co-author of several technical papers.Cyril Royere was born in France, in 1972. He received the M.S. degree in 1995 from the university of Reims. In 2002 he received the Ph.D. degree from the university of Technology of Compiegne. In his thesis, he describes the origins of the conflict which appears when combining of various sources of imperfect information within the framework of the belief theory. Since 2002, he is a researcher at INRETS, into the perception team of the LIVIC department (Laboratory on interactions between vehicles, Infrastructure and drivers) and works on automated highway and on on-board driving assistance systems. His main work deals with obstacles detection using data fusion. He is involved for multi-sensor fusion tasks in several European and French projects dealing with intelligent vehicles (CARSENSE, MICADO, ARCOS).He is the author and co-author of several technical papers.Dominique Gruyer was born in France, in 1969. He received the M.S. and Ph.D. degree respectively in 1995 and 1999 from the university of Technology of Compiëgne.Since 2001, he is a researcher at INRETS, into the perception team of the LIVIC department (Laboratory on interactions between vehicles, Infrastructure and drivers) and he works on the study and the development of multi-sensor/sources association, combination and fusion. His works enter into the conception of on-board driving assistance systems and more precisely on the carry out of multi-obstacle detection and tracking, extended perception, accurate localization, anti-collision system, collision mitigation. He is involved for multi-sensor fusion tasks in several European and French projects dealing with intelligent vehicles (CARSENSE, MICADO, ARCOS). He is a multi-sensor fusion expert for several companies, teaches at Orsay (Paris XI), Ecole Nationale des Ponts et Chaussées and University of Technologie of Compiëgne.He is the author and co-author of several technical papers.Didier Aubert was born in France, in 1963. He received the M.S. and Ph.D. degree respectively in 1985 and 1989 from the university of Grenoble. From 1989–1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was project leader of several projects dealing with computer vision (Multi-resolution, color, motion detection, 3D reconstruction, 3D location, Shape recognition, automatic shape modelling, object tracking), mobile robotic (calibration, roads following, free space computation) and manipulator robotic (calibration, automatic surface tracking). He was also working as an expert for companies on the face recognition, 3D location and roads following topics. He is currently a researcher at INRETS since 1995, manages the perception team of the LIVIC department and works on car traffic monitoring, crowd monitoring, incidents detection, automated highway and on on-board driving assistance systems. He is an image processing expert for several compagnies, teaches at Jussieu (Paris VI), Ecole Nationale des Ponts et Chaussées, Ecole Nationale Supérieure des Télécommunications, Orsay (Paris XI) and is at the editorial board of RTS (Research-Transport-Safety).He is the author and co-author of several technical papers and has participated to the redaction of the books named “Robotique mobile” and “la route automatisée.”     

激光扫描传感器R2000的应用

LI Shao(Shanghai Pepperl+Fuchs Automation Trading Co.,Ltd.,Shanghai, 200436,China)