A surface reconstruction algorithm for topology optimization

For mechanical structural design, topology optimization is often utilized. During this process, a topologically optimized model must be converted into a parametric CAD solid model. The key point of conversion is that a discretized shape of a topologically optimized model must be smoothed, but features such as creases and corners must be retained. Thus, a surface reconstruction algorithm to produce the parametric CAD solid model from a topologically optimized model is proposed in this paper. Our presented algorithm consists of three parts: (1) an enclosed isosurface geometry from which the topologically optimized model is generated, (2) features detected and (3) the parametric CAD solid model reconstructed as biquartic surface splines. In order to generate an enclosed isosurface model effectively, we propose an algorithm based upon the marching cubes method to detect elements intersected by an isosurface. After generating an enclosed isosurface model, we produce biquartic surface splines. By applying our algorithm to an enclosed isosurface model, it is possible to produce smoothed biquartic surface splines with features retained. Some examples are shown and the effectiveness of our algorithm is discussed in this paper.     

基于拟牛顿法和块稀疏重建的TWR成像算法

多径效应环境中边墙位置的不确定性给穿墙雷达系统的目标定位和高分辨率成像的要求带来很大的挑战。针对上述问题,在对穿墙雷达多径回波信号进行合理建模的基础上,提出一种基于拟牛顿法和块稀疏重建的成像算法。所提成像算法在精确重建边墙位置的基础上具有成像目标定位准确,无虚假目标的优点,数值仿真实验结果验证了所提成像算法的有效性和正确性。     

高炉燃烧料面合成孔径雷达双聚焦成像算法

钢铁生产中的料位和料形是冶炼过程控制的重要指标,基于合成孔径雷达(SAR)原理的微波成像装置可有效提取热态径向料面特征.针对几何形态复杂,回波信号突变性强,甚至会出现遮蔽效应导致雷达失波的料面中心部分,本文建立了中心区域双聚焦测量成像系统.选定炉顶风罩位置对称安装两套雷达,电机控制雷达天线匀速摆动获取二维坐标矩阵,用重采样插值算法将其转换成像素点均匀的矩形灰度图像;根据尺寸参数确定炉心扫描重叠区间,并构建料面中心双聚焦融合算法(DfSAR)拼接双图像.与均值融合相比,图像互信息提高10.43%,清晰度改善23.91%.最后,采用雷达恒虚警率(CFAR)目标检测算法有效滤除高炉内粉尘颗粒物对料面图像的干扰.     

A new mesh-growing algorithm for fast surface reconstruction

This paper presents a new high-performance method for triangular mesh generation based on a mesh-growing approach. Starting from a seed triangle, the algorithm grows the triangular mesh by selecting a new point based on the Gabriel 2—Simplex criterion. This criterion can be considered to be a good approximation of the 2D Delaunay if the point cloud is well-sampled and not too rough. The performance of the proposed method is compared with that of the Cocone family and that of Ball Pivoting as regards the tessellation rate and the quality of the surface being generated from some benchmark point clouds and artificially noised test cases. The results are analysed and critically discussed.     

A greedy Delaunay-based surface reconstruction algorithm

In this paper, we present a new greedy algorithm for surface reconstruction from unorganized point sets. Starting from a seed facet, a piecewise linear surface is grown by adding Delaunay triangles one by one. The most plausible triangles are added first and in such a way as to prevent the appearance of topological singularities. The output is thus guaranteed to be a piecewise linear orientable manifold, possibly with boundary. Experiments show that this method is very fast and achieves topologically correct reconstruction in most cases. Moreover, it can handle surfaces with complex topology, boundaries, and nonuniform sampling.     

The ball-pivoting algorithm for surface reconstruction

The Ball-Pivoting Algorithm (BPA) computes a triangle mesh interpolating a given point cloud. Typically, the points are surface samples acquired with multiple range scans of an object. The principle of the BPA is very simple: Three points form a triangle if a ball of a user-specified radius p touches them without containing any other point. Starting with a seed triangle, the ball pivots around an edge (i.e., it revolves around the edge while keeping in contact with the edge's endpoints) until it touches another point, forming another triangle. The process continues until all reachable edges have been tried, and then starts from another seed triangle, until all points have been considered. The process can then be repeated with a ball of larger radius to handle uneven sampling densities. We applied the BPA to datasets of millions of points representing actual scans of complex 3D objects. The relatively small amount of memory required by the BPA, its time efficiency, and the quality of the results obtained compare favorably with existing techniques     

磁共振成像重建的新算法

提出了一种高效的磁共振成像重建算法,将磁共振成像重建看作标准的线性求逆问题,基于变量分离技术重新建立线性求逆问题的目标函数,用交替最小化方法处理新目标函数的优化问题.新目标函数的优化包含两个交替的过程:一个凸的光滑函数的优化和一个凸的非光滑函数的优化.为处理非光滑函数的优化问题,引入投影算法对其求解.实验结果表明了该磁共振成像重建算法的有效性,与同类算法性比,重建的磁共振图像的均方误差(MSE)最小,重建的速度最快.     

超宽带步进变频连续波雷达近场成像算法

为了实现超宽带步进变频连续波雷达近场区高分辨率快速成像,提高成像的分辨率,根据步进变频连续波信号发射与传播的特点,采用角谱分析方法,通过对电磁波波动方程进行推导,提出一种适用于超宽带步进变频连续波雷达的成像算法,该算法省去了匹配滤波过程,成像准确。采用HFSS三维电磁场仿真软件进行建模仿真,在仿真结果中采集数据验证成像算法的可行性。结果表明,成像图像中目标能量集中,分辨率高,对于采用的频率范围0.5～1.5GHz,带宽为1GHz的发射信号,理论分辨率为0.15m,实际得到的分辨率约为0.2m。     

A novel compression framework of the dense point-cloud model for cultural heritage artifacts

Multimedia Tools and Applications - With the help of laser scanner, the accurate digital information of cultural relics can be obtained. However, how to transfer the enormous and dense data by an...     

三角测距激光雷达的光斑定位算法研究

为了降低激光雷达测距系统的光斑信号噪声,提高系统的测距精度,对属性距离加权平均滤波及灰度质心法进行改进,提出一种应用于激光雷达系统的改进算法。以曲率为属性的属性距离加权平均滤波在去噪的同时很好地突出了光斑的峰值点。通过多次迭代计算灰度质心的求质心方法,进一步地提高光斑中心的定位精度,还解决了一般平方加权质心法容易受到噪声影响的问题。在MATLAB仿真环境中对实际采集的数据进行处理,实验表明本文算法对于4μs的像素单元可以取得0.05 pix的定位精度,并具有较好的稳定性。     

多尺度图割曲面重建算法

针对图割曲面重建算法计算量过大的难题, 根据代数多栅理论对图割计算过程进行多尺度分解, 仅对最后一级进行最大流计算, 其他级的标记值通过插值得到。首先, 根据点云法向和重建曲面法向的一致性构建能量函数; 其次, 将能量函数映射到三维权重图的顶点和边上; 然后, 定义顶点间的一致性并由此构造抽取矩阵, 以决定哪些图的顶点参与图割运算; 之后, 构造插值矩阵, 将最后一级图割计算结果逐级插值到第一级; 最后, 利用步进立方体算法得到重建曲面的三角网格表示。实验结果表明, 与窄带图割算法相比, 本方法计算速度更快, 当图的顶点数越多时速度提高得越多; 对于不均匀采样的点云数据, 重建效果更好; 其他情况下两者效果相当。     

A novel 3D morphing approach for tooth occlusal surface reconstruction

Reconstruction of the tooth occlusal surface is an important aspect of dental CAD systems. The design surface should fit to the existing tooth articulation and keep the morphological features of the generic teeth. This paper presents the use of a 3D morphing technique to reconstruct the missing inlay or crown occlusal surface. This method involves three necessary steps of tooth cavity contour extraction, feature points identification and tooth surface deformation. Because the missing occlusal surface is often determined by the outline of the cavity inside the remaining tooth, the cavity contour is tracked firstly by a 3D optimal path searching algorithm. Then through identifying a number of corresponding feature points on the standard tooth and the remaining tooth by a Snake model algorithm, the method uses a mapping function called Radial Basis Function (RBF) to define the spatial relations of all points in both teeth, and interpolate the intermediate feature positions, such that the standard tooth surface is deformed into alignment, and the missing surface is determined. This presents a direct and simple method to automatically reconstruct the occlusal surface. The corresponding features are fully considered in the morphing algorithm, consequently the morphological features of the tooth are well retained.     

面向非均匀采样点集的3维表面重建算法

针对非均匀采样点集,提出一种改进的3维表面重建方法。该方法将整个点集进行空间划分,缩小近邻点的搜索范围,减少搜索时间;在确定近邻点时,先计算几何近邻点,然后通过求方向性点并构造最小生成树的方法,确定拓扑近邻点;最后通过将拓扑近邻点投影到局部切平面上,利用约束条件对投影点进行三角剖分,并将剖分得到的顶点连接关系映射到3维空间中,实现3维表面重建。实验结果表明,改进后的算法运行效率高、重建效果好、广泛适用于非均匀采样点集的表面重建。     

A pointwise smooth surface stereo reconstruction algorithm without correspondences

This paper describes an algorithm for 3D reconstruction of a smooth surface with a relatively dense set of self-similar point features from two calibrated views. We bypass the usual correspondence problem by triangulating a point in space from all pairs of features satisfying the epipolar constraint. The surface is then extracted from the resulting point cloud by taking advantage of the statistical and geometric properties of the point distribution on the surface. Results are presented for computer simulations and for a laboratory experiment on a silicon gel phantom used in a breast cancer screening project.     

Through-the-wall radar imaging exploiting Pythagorean apertures with sparse reconstruction

Through-the-wall radar imaging (TWRI) is receiving a considerable attention recently due to its diverse applications. One of the impinging challenges is the multipath propagation from the surrounding environment and even targets themselves. Multipath propagation produces ghost targets which populate the scene and not only create confusion with genuine targets but deteriorate the performance of compressive sensing (CS) algorithms. Unlike genuine targets, ghost locations are aspect dependent. Successful exploitation of this feature is dictated by the subarray selection modality. Up to this far, random multiple subarrays selection is the practice in exploiting aspect dependence. This paper suggests new subarray configurations based on Pythagorean triple which is made of pairwise coprime numbers that can enhance ghost suppression process and improve image resolution. The sensing matrices of the proposed subarrays are developed and analyzed. The paper investigates the effectiveness of generating the images from all the elements in the array as opposed to generating the images by processing designed subarrays individually and then combining the results. This comparison is done in view of multipath ghost suppression exploiting aspect dependence feature. Results based on synthesized data and electromagnetic propagation simulator show the effectiveness of the proposed arrays.     

基于快速Delaunay三角化的散乱点曲面重建算法

针对现有三维重建算法速度较慢的问题,提出了一种基于快速Delaunay三角化的散乱数据点的三维重建算法。首先,提出一种新的平面Delaunay三角化插入点目标三角形定位算法,利用插入点的方向搜索线与三角形是否相交以及交点个数加速目标三角形定位,不用额外判断点是否在三角形内;其次,自动检测曲面漏洞,利用凸壳的边界拼接方法进行漏洞弥补。实验结果表明,本算法不仅能较好地重建出三维模型,而且有较高的效率。     

基于改进OMP的超宽带穿墙雷达稀疏成像方法

在超宽带穿墙雷达成像应用中,压缩感知理论应用可以获得高分辨率稀疏成像。但这必须建立在目标恰好落在预设网格点的前提条件下,一旦目标偏离预设网格点,目标像会发生偏移,甚至还会产生虚假像。本文提出一种基于梯度优化的贝叶斯假设检验正交匹配追踪(GBTOMP)稀疏成像方法。该方法以传统正交匹配追踪(OMP)为基础,从预设网格点空间位置出发,以梯度优化的最速上升方法搜索到目标真实空间位置,并由此修正模型中的感知矩阵,再利用修正后的感知矩阵恢复目标散射系数。考虑到正交匹配追踪会带来冗余下标,利用贝叶斯假设检验设置一个合适的门限去冗余以保证目标真实像的准确恢复。仿真和实验结果表明,该方法校正了目标偏离预设网格所带来的模型误差,稀疏成像效果明显改善。     

三维散乱点云快速曲面重建算法

提出了一种基于Delaunay三角剖分的三维散乱点云快速曲面重建算法。算法首先计算点云的Delaunay三角剖分, 从Delaunay四面体提取初始三角网格, 根据Voronoi体元的特征构造优先队列并生成种子三角网格, 然后通过区域生长的方式进行流形提取。实验结果表明, 该算法可以高效、稳定地重构具有复杂拓扑结构、非封闭曲面甚至是非均匀采样的点云数据。与传统的基于Delaunay的方法比较, 该算法仅需要进行一次Delaunay三角剖分, 无须极点的计算, 因此算法的重构速度快。