Algorithms for accurate 3D registration of neuronal images acquired by confocal scanning laser microscopy

This paper presents automated and accurate algorithms based on high‐order transformation models for registering three‐dimensional (3D) confocal images of dye‐injected neurons. The algorithms improve upon prior methods in several ways, and meet the more stringent image registration needs of applications such as two‐view attenuation correction recently developed by us. First, they achieve high accuracy (≈ 1.2 voxels, equivalent to 0.4 µm) by using landmarks, rather than intensity correlations, and by using a high‐dimensional affine and quadratic transformation model that accounts for 3D translation, rotation, non‐isotropic scaling, modest curvature of field, distortions and mechanical inconsistencies introduced by the imaging system. Second, they use a hierarchy of models and iterative algorithms to eliminate potential instabilities. Third, they incorporate robust statistical methods to achieve accurate registration in the face of inaccurate and missing landmarks. Fourth, they are fully automated, even estimating the initial registration from the extracted landmarks. Finally, they are computationally efficient, taking less than a minute on a 900‐MHz Pentium III computer for registering two images roughly 70 MB in size. The registration errors represent a combination of modelling, estimation, discretization and neuron tracing errors. Accurate 3D montaging is described; the algorithms have broader applicability to images of vasculature, and other structures with distinctive point, line and surface landmarks.     

基于平面基线靶标的视觉测量数据拼接方法

针对视觉测量中三维数据的拼接问题,提出一种基于平面基线靶标的数据拼接方法。该方法利用平面基线靶标提供特征点,建立视觉传感器在相邻位置坐标系旋转矩阵和平移矢量各参数的优化目标函数,通过Levenberg—Marquardt优化算法求解出旋转矩阵和带有未知系数平移矢量。在此基础上,利用平面靶标上的基线长度确定平移矢量系数,从而求得数据拼接矩阵。利用平面靶标上100个点进行拼接试验,计算出x、y和z坐标拼接RMS误差分别为0．038 mm、0．022 mm和0．135 mm。结果表明该方法柔性好,适用范围广。     

基于复合Zernike矩相角估计的图像配准

提出了一种基于复合Zernike矩相角估计的图像配准方法.首先,利用尺度不变检测子Harris-laplace检测图像中的兴趣点作为初始特征点,计算以兴趣点为中心、邻域具有尺度不变性的Zernike矩;提出一种鲁棒的相角估计方法,用于估计两个归一化区域的旋转角度值.然后,利用Zernike矩的幅值和相角信息,通过比较每个兴趣点邻域Zernike矩的相似度提取出初始匹配点.最后,提出一种迭代角度修正算法用于精确估计变换参数,并对输入图像进行几何变换后将两幅图像配准.实验结果表明,该算法可在尺度缩放、任意角度旋转以及噪声等复杂条件下实现图像的高精度配准.当旋转角度误差小于20°时,图像的平均覆盖率达到94.125％,有效降低了误匹配的概率.     

Analytic differential approach for robust registration of rat brain histological images

Image registration is an important topic in medical image analysis. It is usually used to reconstruct 3D structure of tissues from a series of microscopic images. However, a variety of inherent factors may result in great differences between acquired slices during imaging even if they are adjacent. The common differences include the color difference and geometry discrepancy, which make the registration problem a difficult challenge. In this study, we propose a robust registration method to automatically reconstruct 3D volume data of the rat brain. It mainly consists of three procedures, including multiscale wavelet-based feature extraction, analytic robust point matching (ARPM), and registration refinement with feature-based modified Levenberg-Marquardt algorithm (FMLM). The product of gradient moduli in multi-scales is used to decide if extracted feature points are true according to the characteristic that features could exist in multiscale. The ARPM registration algorithm is proposed to speedily accomplish the registration of two point sets with different size by simultaneously evaluating the spatial correspondence and geometrical transformation. In addition, a FMLM method is also proposed to further refine registration results and achieve subpixel accuracy. The FMLM method converges much faster than most other methods due to its feature-based and nonlinear characteristic. The performance of proposed method is evaluated by comparing it with well-known thin-plate spline robust point matching (TPS-RPM) algorithm. The results indicate that ARPM-FMLM algorithm is a robust and fast method in image registration.     

6-DOF MOTION AND CENTER OF ROTATION ESTIMATION BASED ON STEREO VISION

A new motion model and estimation algorithm is proposed to compute the general rigid motion object＇s 6-DOF motion parameters and center of rotation based on stereo vision. The object＇s 6-DOF motion model is designed from the rigid object＇s motion character under the two defined reference frames. According to the rigid object＇s motion model and motion dynamics knowledge, the corresponding motion algorithm to compute the 6-DOF motion parameters is worked out. By the rigid object pure rotation motion model and space sphere geometry knowledge, the center of rotation may be calculated after eliminating the translation motion out of the 6-DOF motion. The motion equations are educed based on the motion model and the closed-form solutions are figured out. To heighten the motion estimation algorithm＇s robust, RANSAC algorithm is applied to delete the outliers. Simulation and real experiments are conducted and the experiment results are analyzed. The results prove the motion model＇s correction and algorithm＇s validity.     

Registration of serial sections of mouse liver cell nuclei

Image registration of biological tissue is essential for 3D reconstruction, which is important for visualizing and quantifying the 3D relationships between internal structures of an object. The biological role of DNA organization, which is an extremely complex 3D architecture within the cell nucleus, has come into focus since it has become clear that the chromatin structure in itself functions as a regulator of DNA. Thus, 3D reconstruction of cell nuclei based on consecutive series of high-resolution ultrathin slices may provide new information about the chromatin structure and its organizational changes during carcinogenesis. This work focuses mainly on the problem of registering successive serial transmission electron micrographs of ultrathin sections of mouse liver cell nuclei to analyse the 3D chromatin structure. A five-step semiautomatic interactive registration method is proposed. The first two steps of the procedure correct the rotation and translation components by using the phase correlation. The third, fourth and fifth steps correct the global distortion, employing a point mapping method based on different ways of selecting the control points. In step three, the control points were automatically computed by phase correlating corresponding subimages of the reference and sensed image. A semiautomatic method is used in the fourth step to select the control points, i.e. an automated method for computing the centre of mass of manually identified anatomical structures in neighbouring slices. For the sections which could not be properly corrected by the four steps, a final step is introduced, where control points are manually selected in the reference and sensed images. An algorithm is proposed to examine the spatial distribution of selected control points. Four sets of serial sections of mouse liver cell nuclei, each with approximately 100 sections, are registered by the proposed method and also registered manually for the comparison of registration accuracy. Artificial X–Z and Z–Y sections of registered series were visually compared for the smoothness of the nuclear membrane. To quantify the registration accuracy and the extent of registration, the correlation coefficient (C) and the overlap index (C₀) were computed over the registered structure of interest. In addition to the visual comparison and the comparison of C and C₀, the registered serial sets were compared by 3D GLCM-based texture features in the Z direction. The results demonstrate that the proposed semiautomatic registration technique achieved accurate results comparable to the manual registration. The proposed registration method relies only on the operator for rough pinpointing of cellular structures. Therefore, it should provide better reproducibility, and allow the user to operate the system faster and in a more relaxed manner than in a manual registration.     

基于相对相位直方图的数字表面模型数据与遥感图像配准

针对数字表面模型（DSM）数据与可见光遥感图像信息融合的实际需求,提出了一种基于一致点漂移算法（CPD）与相对相位直方图（RPH）的两级配准策略来实现上述数据与图像的自动配准。首先,利用Canny算子提取图像边缘,将边缘点作为CPD算法的输入,实现两幅图像的粗匹配,从而得到初始对应点集并估算尺度因子;然后,定义了一种鲁棒且具有旋转、平移不变性的区域变化信息描述子-RPH,其在粗匹配结果的保障下还可以实现尺度不变性;最后,根据尺度因子在两幅图像中分别定义圆环模板,并利用RPH测度完成DSM图像与可见光遥感图像精配准。实验结果显示,使用RPH测度进行精配准后,基于CPD算法的粗匹配结果得到了有效校正,在数据自身存在透视失真情况下,算法配准误差约为2 pixel,能够满足DSM数据与遥感图像信息融合的需求。     

注射液杂质智能灯检机关键模块设计及仿真

针对注射液杂质全自动智能灯检机中检测平台的核心运动单元的设计进行了详细的论述,并详细介绍了灯检机的工作原理。为了采集到准确清晰的注射液杂质图像,对灯检机机械系统中检测平台的关键检测模块进行设计与分析,其主要包括回转组件、夹具组件和同步带轮组件等关键部件。综合应用三维实体造型CAD软件和机械系统动力学分析软件ADAMS建立了所设计的灯检机的虚拟样机,并通过初步运动仿真分析,验证了所设计机构的合理性以及该设计的意义。     

基于抖动补偿技术的印刷品图像配准方法研究

在实际的印刷品缺陷检测过程中,存在因相机支架的颤动而导致标准印刷图像和待检测图像在空间位置上配准不精确的问题。为此,在图像去抖动技术的基础上,提出了一种融合SURF(speeded-up robust features)和ORB(oriented FAST and rotated BRIEF)的运动估计算法。首先,基于SURF算法提取标准印刷图像和待检测图像的特征点;其次,基于ORB算法对提取的特征点进行描述和匹配;再次,将正确匹配的特征点通过仿射模型来求取全局运动矢量;最后,通过求得的全局运动矢量来补偿图像,并完成待检测图像与标准印刷图像的配准。针对待测图像存在的平移、尺度和旋转三种不同变化,分别采用SURF-ORB、ORB和SIFT(scale-invariant feature transform)的运动估计算法进行了性能分析。结果表明,SURFORB的特征点匹配对数量最多,匹配效果最好,SURB-ORB的运动估计时间控制在毫秒级别,满足现代印刷品缺陷检测的实时性要求。因此,融合SURF和ORB的运动估计算法能够对图像进行精确、实时的配准。     

基于直线光流场的三维检测新方法

提出了基于直线光流场的三维检测计算方法。在透视投影下,将表示二维直线的参数对时间的导数定义成直线光流场,详细推导出基于直线光流场检测三维刚体运动参数的模型。使用最小二乘法,求出刚体的三维旋转运动参数、平移运动参数和空间直线坐标,从而实现了刚体的三维检测。该方法利用单目图像序列中连续3幅图像的2对直线光流,能够检测出物体的运动参数和结构参数,有助于全面检测和识别物体。多组实验表明该方法是稳定的,具有较好的鲁棒性能。     

基于ASODVS的全景相机运动估计及管网3D重构技术

针对地下管网的空间三维测量、三维形貌重构难等问题,提出了一种基于主动式全方位视觉传感器(ASODVS)的相机运动估计及管网3D重构解决方案。通过携带有ASODVS的管道机器人进入管道内部,实时获取管道内壁纹理全景图像和全景激光扫描图像;首先对全景激光扫描图像处理解析出投射在管道内壁上的激光中心点,通过计算得到管道横截面的点云数据;另一方面,对全景纹理图像进行处理,首先利用快速鲁棒性特征(SURF)算法快速提取特征点并进行匹配,然后采用随机抽样一致性(RANSAC)算法去除误匹配点,接着利用全景相机的极几何原理估计相机运动位姿,并利用光束法平差(BA)进行优化,最后利用相机运动位姿将相机坐标系下的点云坐标实时转换到世界坐标系下,完成对地下管网的三维重构。实验结果表明,所提出的方案能够精确估计相机运动位姿,实时对管道内部进行三维重构,实现了管道检测机器人边行走、边采集数据、边检测分析处理、边三维建模的设计目标。     

HP6机器人运动学动力学分析及运动仿真研究

提出了hp6机器人的基坐标和运动坐标系统和运动学动力学模型,导出了基于D-H参数法的该机器人运动方程和拉格朗日动力学方程,并完成了Matlab环境下的运动学仿真分析,所得结果可应用于机器人关节驱动装置设计及机器人轨迹规划的动力学优化设计.     

Three-Dimensional Reconstruction of Welding Pool Surface by Binocular Vision

Current research of binocular vision systems mainly need to resolve the camera's intrinsic parameters before the reconstruction of three-dimensional(3D)objects.The classical Zhang'calibration is hardly to calculate all errors caused by perspective distortion and lens distortion.Also,the image-matching algorithm of the binocular vision system still needs to be improved to accelerate the reconstruction speed of welding pool surfaces.In this paper,a preset coordinate system was utilized for camera calibration instead of Zhang'calibration.The binocular vision system was modified to capture images of welding pool surfaces by suppressing the strong arc interference during gas metal arc welding.Combining and improving the algorithms of speeded up robust features,binary robust invariant scalable keypoints,and KAZE,the feature information of points(i.e.,RGB values,pixel coordinates)was extracted as the feature vector of the welding pool surface.Based on the characteristics of the welding images,a mismatch-elimination algorithm was developed to increase the accuracy of image-matching algorithms.The world coordinates of match-ing feature points were calculated to reconstruct the 3D shape of the welding pool surface.The effectiveness and accuracy of the reconstruction of welding pool surfaces were verified by experimental results.This research proposes the development of binocular vision algorithms that can reconstruct the surface of welding pools accurately to realize intelligent welding control systems in the future.     

Registration of phase‐contrast images in propagation‐based X‐ray phase tomography

X‐ray phase tomography aims at reconstructing the 3D electron density distribution of an object. It offers enhanced sensitivity compared to attenuation‐based X‐ray absorption tomography. In propagation‐based methods, phase contrast is achieved by letting the beam propagate after interaction with the object. The phase shift is then retrieved at each projection angle, and subsequently used in tomographic reconstruction to obtain the refractive index decrement distribution, which is proportional to the electron density. Accurate phase retrieval is achieved by combining images at different propagation distances. For reconstructions of good quality, the phase‐contrast images recorded at different distances need to be accurately aligned. In this work, we characterise the artefacts related to misalignment of the phase‐contrast images, and investigate the use of different registration algorithms for aligning in‐line phase‐contrast images. The characterisation of artefacts is done by a simulation study and comparison with experimental data. Loss in resolution due to vibrations is found to be comparable to attenuation‐based computed tomography. Further, it is shown that registration of phase‐contrast images is nontrivial due to the difference in contrast between the different images, and the often periodical artefacts present in the phase‐contrast images if multilayer X‐ray optics are used. To address this, we compared two registration algorithms for aligning phase‐contrast images acquired by magnified X‐ray nanotomography: one based on cross‐correlation and one based on mutual information. We found that the mutual information‐based registration algorithm was more robust than a correlation‐based method.     

旋转运动模糊的实时恢复

提出了一种旋转运动模糊恢复算法,用来解决航空成像时旋转运动模糊的实时恢复问题.对旋转运动模糊这种具有异速像移的空间变化模糊进行了分析,并推导出旋转运动模糊的数学模型.用基于Bresenham画圆法的坐标转换方法将旋转圆弧上的空间变化模糊转变为常见的线性空间不变模糊,并使用一维维纳滤波对圆弧轨迹上的像素点进行模糊恢复.实验结果显示:本文算法在GPU处理平台下用3.31 ms即能恢复一帧1 024×1 024,8 bit旋转运动模糊图像,且极好地恢复了图像上的细节信息,恢复图像的峰值信噪比(PSNR)为28.76.算法的速度及效果表明本文所提出的算法具有较大的实用价值.     

基于 Marker-SLAM 的视触觉增强现实交互算法

视触觉增强现实是将触觉感知加入到增强现实中的一种新技术。 不仅可以融合真实场景和虚拟对象,还能实现视觉和 触觉的同步感知。 基于 3D Systems Touch 触觉设备提出一种新的视触觉交互算法。 首先,基于 Marker-SLAM 算法搭建增强现 实环境,用于实时获得相机在地图中的位姿;其次,为了将触觉信息融入到增强现实环境中,提出基于无跟踪器的触控笔尖端姿 态优化算法;最后,分别采集测量点在触觉和世界坐标系中的三维信息,通过确定两个坐标系间的刚性变换,将触觉设备的正向 运动模型映射到增强现实空间中。 所提出的跟踪注册方法的注册准确率均达到 90% 以上,与基于跟踪器的方法相比,所提出的 姿态优化算法获得的校正位置的平均误差为 2. 3±0. 2 mm。     

基于单经纬仪的视觉测量三维数据拼接方法

本文针对大型自由曲面三维视觉测量中的数据拼接问题，建立了经纬仪透视投影模型，提出了以平面靶标为中介坐标系，以经纬仪坐标系为全局坐标系的三维数据拼接方法。在大型自由曲面的若干测量子区域附近放置一个平面靶标，通过视觉传感器拍摄平面靶标上的特征点，求得视觉传感器坐标系到靶标坐标系的变换矩阵；通过经纬仪观测靶标上的特征点，求得靶标坐标系到经纬仪坐标系的变换矩阵。因此，可求得视觉传感器坐标系到经纬仪坐标系的变换矩阵。将视觉传感器所测得的各子区域的三维数据统一到了经纬仪坐标系下，即完成了大型自由曲面的全局测量。经实验验证，数据拼接的RMS误差小于0．487mm。     

应用自适应模拟退火和多分辨率搜索实现医学超声图像的拼接

为提高图像拼接的成功率,提出了一种基于自适应模拟退火和多分辨率搜索策略的图像自动拼接新方法。该新算法先自适应地选取配准区域,再以互信息为相似度评价标准,结合自适应模拟退火和多分辨率搜索策略的思想分别进行图像平移和旋转参数的全局优化和局部搜索,最后实现图像的拼接。通过对含噪声数字图像和医学超声图像进行的24次模拟拼接实验表明,该新算法较传统的多分辨率直接搜索法有精度高、速度快和抗噪声能力强的优点。由于结合了模拟退火算法的高精度和多分辨率搜索法的高效率,改进后的图像拼接算法将拼接成功率提高了12.5%,并将运算时间控制在可接受的范围内。     

转台误差对数字天顶仪轴系误差的影响

针对数字天顶仪在定位过程中存在的的轴系偏差,研究了如何对光轴与旋转轴、旋转轴与垂直轴之间的角度偏差进行补偿的方法。为了高精度地解算出测站点位置垂直轴的天文坐标,采用对称位置的两幅星图直接解算旋转轴的坐标,从而避免了光轴与旋转轴之间的补偿。采用双轴倾角仪测量倾角,并对旋转轴进行倾角补偿得出垂直轴的位置坐标。考虑进行轴系补偿时,转台误差会对旋转轴坐标和倾角补偿造成影响,分别研究了转台误差对于旋转轴以及倾角补偿的影响,并得出了转台误差的范围。实验结果表明:当测站点纬度的绝对值小于或等于88.3°时,转台误差必须小于或等于35″;当测站点纬度的绝对值大于88.3°时,转台误差值要小于|1 166.8cosδ|″。在对称位置解算测站点位置坐标时,必须提高转台的精度,以减小转台误差对于定位精度的影响。