A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves

Parametric curves such as Bézier and B-splines, originally developedfor the design of automobile bodies, are now also used in image processing andcomputer vision. For example, reconstructing an object shape in an image,including different translations, scales, and orientations, can be performedusing these parametric curves. For this, Bézier and B-spline curves can be generatedusing a point set that belongs to the outer boundary of the object. Theresulting object shape can be used in computer vision fields, such as searchingand segmentation methods and training machine learning algorithms. Theprerequisite for reconstructing the shape with parametric curves is to obtainsequentially the points in the point set. In this study, a novel algorithm hasbeen developed that sequentially obtains the pixel locations constituting theouter boundary of the object. The proposed algorithm, unlike the methods inthe literature, is implemented using a filter containing weights and an outercircle surrounding the object. In a binary format image, the starting point ofthe tracing is determined using the outer circle, and the next tracing movementand the pixel to be labeled as the boundary point is found by the filter weights.Then, control points that define the curve shape are selected by reducing thenumber of sequential points. Thus, the Bézier and B-spline curve equationsdescribing the shape are obtained using these points. In addition, differenttranslations, scales, and rotations of the object shape are easily provided bychanging the positions of the control points. It has also been shown that themissing part of the object can be completed thanks to the parametric curves.

Reconstruction of probabilistic S-N curves under fatigue life following lognormal distribution with given confidence

When the historic probabilistic S-N curves are given under special survival probability and confidence levels and there is no possible to re-test, fatigue reliability analysis at other levels can not be done except for the special levels. Therefore, the wide applied curves are expected. Monte Carlo reconstruction methods of the test data and the curves are investigated under fatigue life following lognormal distribution. To overcome the non-conservative assessment of existent man-made enlarging the sample size up to thousands, a simulation policy is employed to address the true production where the sample size is controlled less than 20 for material specimens, 10 for structural component specimens and the errors matching the statistical parameters are less than 5 percent. Availability and feasibility of the present methods have been indicated by the reconstruction practice of the test data and curves for 60Si2Mn high strength spring steel of railway industry.

RECONSTRUCTION OF SYMMETRIC B-SPLINE CURVES AND SURFACES

A method to reconstruct symmetric B-spline curves and surfaces is presented. The symmetry property is realized by using symmetric knot vector and symmetric control points. Firstly, data points are divided into two parts based on the symmetry axis or symmetry plane extracted from data points. Then the divided data points are parameterized and a symmetric knot vector is selected in order to get symmetric B-spline basis functions. Constraint equations regarding the control points are deduced to keep the control points of the B-spline curve or surface to be symmetric with respect to the extracted symmetry axis or symmetry plane. Lastly, the constrained least squares fitting problem is solved with the Lagrange multiplier method. Two examples from industry are given to show that the proposed method is efficient, robust and able to meet the general engineering requirements.

Lutetium in prostate cancer: Reconstruction of patient-level data from published trials and generation of a multi-trial Kaplan-Meier curve

BACKGROUND Lutetium has been shown to be an important potential innovation in pre-treated metastatic castration-resistant prostate cancer.Two clinical trials have evaluated lutetium thus far(therap and vision with 99 and 385 patients,respectively),but their results are discordant.AIM To synthetize the available evidence on the effectiveness of lutetium in pre-treated metastatic castration-resistant prostate cancer;and to test the application of a new artificial intelligence technique that synthetizes effectiveness based on reconstructed patient-level data.METHODS We employed a new artificial intelligence method(shiny method)to pool the survival data of these two trials and evaluate to what extent the lutetium cohorts differed from one another.The shiny technique employs an original reconstruction of individual patient data from the Kaplan-Meier curves.The progression-free survival graphs of the two lutetium cohorts were analyzed and compared.RESULTS The hazard ratio estimated was in favor of the vision trial;the difference was statistically significant(P<0.001).These results indicate that further studies on lutetium are needed because the survival data of the two trials published thus far are conflicting.CONCLUSION Our study confirms the feasibility of reconstructing patient-level data from survival graphs in order to generate a survival statistics.

3D reconstruction of complex curved objects from line drawings

An active research topic in computer vision and graphics is developing algorithms that can reconstruct the 3D surface of curved objects from line drawings. There are a number of algorithms have been dedicated to solve this problem, but they can＇t solve this problem when the geometric structure of a curved object becomes complex. This paper proposes a novel approach to reconstructing a complex curved 3D object from single 2D line drawings. Our approach has three steps： （1） decomposing a complex line drawing into several simpler line drawings and transforming them into polyhedron; （2） reconstructing the 3D wireframe of curved object from these simpler line drawings and generating the curved faces; （3） combining the 3D objects into the complete objects. A number of examples are given to demonstrate the ability of our approach to successfully perform reconstruction of curved objects which are more complex than previous methods.

A Fourth-Order Unstructured NURBS-Enhanced Finite Volume WENO Scheme for Steady Euler Equations in Curved Geometries

In Li and Ren(Int.J.Numer.Methods Fluids 70:742–763,2012),a high-order k-exact WENO finite volume scheme based on secondary reconstructions was proposed to solve the two-dimensional time-dependent Euler equations in a polygonal domain,in which the high-order numerical accuracy and the oscillations-free property can be achieved.In this paper,the method is extended to solve steady state problems imposed in a curved physical domain.The numerical framework consists of a Newton type finite volume method to linearize the nonlinear governing equations,and a geometrical multigrid method to solve the derived linear system.To achieve high-order non-oscillatory numerical solutions,the classical k-exact reconstruction with k=3 and the efficient secondary reconstructions are used to perform the WENO reconstruction for the conservative variables.The non-uniform rational B-splines(NURBS)curve is used to provide an exact or a high-order representation of the curved wall boundary.Furthermore,an enlarged reconstruction patch is constructed for every element of mesh to significantly improve the convergence to steady state.A variety of numerical examples are presented to show the effectiveness and robustness of the proposed method.

MICRO-ROBOT FOR MEASUREMENT AND THREE-DIMENSION RECONSTRUCTION OF MICROPIPES

The presented system consists of field devices, a control system and a host computer system. The field devices, which are composed of an in-pipe micro-robot, a displacement sensor, a curvature sensor, and an inner surface measurement unit, can go into the pipe to get the data of displace- ment and axis curvature, and the shape data of the inner surface. With the conic-shape laser beam shot by the inner surface measurement unit, the intersectional curve between the laser beam and the inner-surface of the tested pipe can be calculated in the local coordination system （LCS） of the inner surface measurement unit. The relation between the LCS and the global coordination system （GCS） can be deduced, too. After the robot reaches the end of the pipe, all measured intersectional curves can be translated into the same coordination system to become a point cloud of the inner surface of the pipe according to the relations between LCS and GCS. Depending on this points cloud, the CAD model of the inner surface of the pipe can be reconstructed easily with reverse engineering tools, and the feature of flaw of the pipe can be obtained with flaw analysis tools.

Randomized Kaczmarz algorithm for CT reconstruction

The order of the projection in the algebraic reconstruction technique(ART)method has great influence on the rate of the convergence.Although many scholars have studied the order of the projection,few theoretical proofs are given.Thomas Strohmer and Roman Vershynin introduced a randomized version of the Kaczmarz method for consistent,and over-determined linear systems and proved whose rate does not depend on the number of equations in the systems in 2009.In this paper,we apply this method to computed tomography(CT)image reconstruction and compared images generated by the sequential Kaczmarz method and the randomized Kaczmarz method.Experiments demonstrates the feasibility of the randomized Kaczmarz algorithm in CT image reconstruction and its exponential curve convergence.

Curve interpolation model for visualising disjointed neural elements

Neuron cell are built from a myriad of axon and denddte structures. It transmits electrochemical signals between the brain and the nervous system. Three-dimensional visualization of neuron structure could help to facilitate deeper understanding of neuron and its models. An accurate neuron model could aid understanding of brain＇s functionalities, diagnosis and knowledge of entire nervous system. Existing neuron models have been found to be defective in the aspect of realism. Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism. In this research, a new reconstruction model comprising of the Bounding Cylinder, Curve Interpolation and Gouraud Shading is proposed to visualize neuron model in order to improve realism. The reconstructed model is used to design algorithms for generating neuron branching from neuron SWC data. The Bounding Cylinder and Curve Interpolation methods are used to improve the connected segments of the neuron model using a series of cascaded cylinders along the neuron＇s connection path. Three control points are proposed between two adjacent neuron segments. Finally, the model is rendered with Gouraud Shading for smoothening of the model surface. This produce a near-perfection model of the natural neurons with attended realism. The model is validated by a group of bioinformatics analysts＇ responses to a predefined survey. The result shows about 82% acceptance and satisfaction rate.

Rollback reconstruction for TDC enhanced perfusion imaging

Tomographic perfusion imaging is a significant imaging modality for stroke diagnosis.However,the low rotational speed of the C-arm(6–8 s per circle)is a challenge for applying perfusion imaging in C-arm cone beam computed tomography(CBCT).Traditional reconstruction methods cannot remove the artifacts caused by the slow rotational speed or acquire enough sample points to restore the time density curve(TDC).This paper presents a dynamic rollback reconstruction method for CBCT.The proposed method can improve the temporal resolution by increasing the sample points used for calculating the TDC.Combined with existing techniques,the algorithm allows slow-rotating scanners to be used for perfusion imaging purposes.In the experiments,the proposed method was compared with other dynamic reconstruction algorithms based on standard reconstruction and the temporal interpolation approach.The presented algorithm could improve the temporal resolution without increasing the X-ray exposure time or contrast agent.

基于计算机视觉的舰船模型三维重建方法

为保证舰船模型三维重建的完整性以及细节程度,提出基于计算机视觉的舰船模型三维重建方法。基于双目立体视觉计算全局舰船目标点云坐标,生成舰船全局的三维点云数据;多视角点云配准方法对该数据进行配准后,输入多尺度特征递归卷积的稠密点云重建网络模型中,通过该模型生成舰船模型三维深度图,在此基础上,利用运动结构法完成舰船深度图中的三维曲线重建,对舰船模型进行颜色渲染,输出舰船模型三维重建结果。测试结果显示,该方法能够完成不同图像之间对应点的可靠匹配,确定各点的坐标位置;三维重建后模型的空间偏差均在0.015以下;能够较好地完成舰船结构的重建,重建后舰船模型的完整性较好,清晰呈现舰船的结构细节。

基于模态分解与LSTM注意表征的测井曲线重构研究

测井曲线记录着地层物理性质随深度变化的幅值范围,是测井与地震资料之间的纽带,对储层岩性分析与识别和后续的油气勘探工程十分重要.然而,在实际的测井过程中仪器故障等原因会造成测井曲线缺失的问题,重新测井不仅价格昂贵而且难以实现.针对地质勘探时测井数据时常缺失的问题,本文提出了一种LSTM(Long Short-Term Memory)注意力表征的测井曲线重构方法.同时,对原始测井信号进行两种模态分解,计算分解后得到模态分量与原始信号之间的相关性,去除冗余分量,实现对缺失的测井曲线高效、高精度的人工补全.将该方法用于声波(ACoustic,AC)与密度(DENsity,DEN)曲线重构实验,并将实验结果与LSTM网络和BP(Back Propagation)神经网络预测的结果进行对比分析.结果表明,LSTM-Attention模型有着更为优异的预测效果,重构后的AC和DEN与原始曲线之间的相关性分别达到了86.8%和74.8%,高于传统LSTM和BP神经网络预测方法.在去除冗余的信号分量后,相关系数分别提高了1.4%和4.0%.同时,本文所提方法预测出的测井曲线具有最低的预测误差.因此,基于LSTM注意表征的网络结构对测井曲线重构具有较好的预测精度.

基于信号分析技术的呼吸机工作状态自动化识别研究

呼吸机作为重症监护室内必不可少的设备,对重症患者起着重要的生命维持和抢救的作用。若呼吸机使用时出现了管路积液的问题且未被发觉,容易造成呼吸机无法正常工作。针对这一问题,以小波变换信号分析技术为基础,设计了呼吸机工作状态自动识别的方案。通过对呼吸波进行小波变换,对时-频信号进行有效提取,分析呼吸机管路是否积液,并通过自动识别保证医护人员对呼吸机工作状态能够实时掌握。实验结果表明,S1重构方式在临床数据以及模拟数据中均能实现较高的准确率,达到96.6%以上,因此该方法切实可行,具有实际应用价值。

基于相机RGB值的光谱反射率重建方法研究

光谱反射率重建技术可实现背景颜色数据准确校正和复制还原,以此为基础可设计实施高融合迷彩,为机动装备在不同背景环境下提供有效防护屏障,具有重要价值。参照光谱成像技术特点,根据颜色形成原理和三刺激值定量计算公式,通过控制单一变量法设计实验方案,提出加权平均光谱反射率重建方法(TWA),利用相机和光谱仪分别获取训练样本的成像系统响应值(RGB)和光谱反射率数据,对所提取的样本RGB值和光谱反射率数据分别采用传统最小二乘法(OLS)、正则化最小二乘法(RLS)、偏最小二乘法(PLS)、主成分分析法(PCA)和本文中提出的加权平均法(TWA)进行光谱反射率重建训练,获得光谱重建矩阵,最后利用光谱重建矩阵对测试样本响应值进行光谱反射率重建,并对实验结果进行分析,对比不同方法的光谱反射率重建效果。研究结果表明,加权平均法在光谱均方根误差SRMSE、平均拟合优度系数GFC、平均色差等指标上效果更优,重建所得光谱反射率精度更高,颜色校正效果更佳。

基于GeoGebra曲线的图案设计及其应用

为提升图案设计效率、丰富图案设计方法,基于GeoGebra软件进行图形提取和二次设计。在GeoGebra软件中调节曲线表达式中的参数数值,使曲线产生动态变化并生成曲线图形。根据图形构成特征进行因子提取,引入形状文法将所提取因子进行重构并构建设计因子库,最后结合图案设计理念对设计因子库的可行性进行验证。研究表明:对GeoGebra曲线进行因子提取与重构,可以将数字化图形的生成方式融入图案设计中;运用设计因子库进行图案设计,将创新图案应用于设计实践,可以实现现代图案的创新设计,丰富图案设计方式在产品中的表达。

改扩建高速公路凸型竖曲线半径不足时出入口设置位置的探讨

早期由于我国经济水平欠发达,整体路网布局欠合理,多数公路在设计时为了降低工程造价而选用较低的平、纵指标,导致目前在改扩建项目中,随着高速公路出、入口数量不断增加,出入口处的纵断面指标多数难以满足《公路路线设计规范》、《公路立体交叉设计细则》要求,大部分设计者仅局限性的运用规范、细则中规定的纵断面指标,并未就满足安全性的前提下对纵断面指标进行验算,导致对既有道路改建较长,工程规模浪费较多,因此有必要对其进行探讨。

Efficient reconstruction of non-simple curves

We present a novel algorithm to reconstruct curves with self-intersections and multiple parts from unorganized strip-shaped points,which may have different local shape scales and sampling densities.We first extract an initial curve,a graph composed of polylines,to model the different structures of the points.Then a least-squares optimization is used to improve the geometric approximation.The initial curve is extracted in three steps:anisotropic farthest point sampling with an adaptable sphere,graph construction followed by non-linear region identification,and edge refinement.Our algorithm produces faithful results for points sampled from non-simple curves without pre-segmenting them.Experiments on many simulated and real data demonstrate the efficiency of our method,and more faithful curves are reconstructed compared to other existing methods.

An Approximating Algorithm on Reconstruction of Complicated Curved Surface

An approximating algorithm on handling 3-D points cloud data was discussed for reconstruction of complicated curved surface. In this algorithm, the coordinate information of nodes both in internal and external regions of partition interpolation was used to realize minimized least squares approximation error of surface fitting. The changes between internal and external interpolation regions are continuous and smooth. Meanwhile, surface shape has properties of local controllability, variation reduction, and convex hull. The practical example shows that this algorithm possesses a higher accuracy of curved surface reconstruction and also improves the distortion of curved surface reconstruction when typical approximating algorithms and unstable operation are used.

拟声波测井曲线在砂岩型铀矿反演中的研究与应用

砂岩型铀矿往往赋存于“泥—砂—泥”、“煤—砂—泥”等互层结构的砂体之中,且埋藏深度较浅,般在300~800 m之间,这就易造成其上覆砂泥岩受地层压实作用力小,导致相邻地层之间声波时差(AC)与密度差异值小,即波阻抗差异小;再加之受测井资料品质及地下构造等综合因素的影响,对研究区地震资料使用声波密度曲线开展叠后波阻抗反演工作时往往只能对剖面上的大套砂体及含砾砂体进行区分.

基于节点日负荷曲线的深度嵌入式聚类及其改进方法对比研究

基于日负荷曲线的负荷节点分类是负荷建模的重要环节,详略得当的分类结果保留了负荷节点的内在特性,可提升电力系统仿真计算的效率。当前基于人工智能的节点聚类方法进展迅速,然而总体上针对数据深层特征提取的适应性仍存在不足。采用了基于改进的深度嵌入式算法的日负荷曲线聚类方法,利用神经网络可有效提取数据的深层特征的能力。进而,提出一种先升维后聚类的改进方法,通过算例对比分析,验证了本文所提算法的可行性,以及所提升维—重构聚类方法的正确性。